Name: Example Talk
Start: 2030-06-01T13:00:00Z
End: 2030-06-01T15:00:00Z
Location: Wowchemy HQ
From 7f58d74822b932635564b53348c2966e3809593d Mon Sep 17 00:00:00 2001
From: ShushanArakelyan <ShushanArakelyan@users.noreply.github.com>
Date: Sun, 10 Dec 2023 07:06:29 +0000
Subject: [PATCH] deploy: 37e1961306502450fe404a4c8f37f8f33ea552cf

---
 404.html                                       | 2 +-
 categories/index.html                          | 2 +-
 category/demo/index.html                       | 2 +-
 "category/\346\225\231\347\250\213/index.html" | 2 +-
 event/index.html                               | 2 +-
 index.html                                     | 2 +-
 index.xml                                      | 4 ++--
 post/getting-started/index.html                | 2 +-
 post/index.html                                | 2 +-
 post/index.xml                                 | 4 ++--
 post/jupyter/index.html                        | 2 +-
 post/writing-technical-content/index.html      | 4 ++--
 project/example/index.html                     | 2 +-
 project/external-project/index.html            | 2 +-
 project/index.html                             | 2 +-
 publication-type/1/index.html                  | 2 +-
 publication-type/2/index.html                  | 2 +-
 publication/bin2vec/index.html                 | 2 +-
 publication/code-transfer/index.html           | 2 +-
 publication/index.html                         | 2 +-
 publication/ns3/index.html                     | 2 +-
 publication_types/index.html                   | 2 +-
 tag/academic/index.html                        | 2 +-
 tag/binary-analysis/index.html                 | 2 +-
 tag/binary-code-representation/index.html      | 2 +-
 tag/deep-learning/index.html                   | 2 +-
 tag/demo/index.html                            | 2 +-
 tag/generalizable-models-for-code/index.html   | 2 +-
 tag/generelization/index.html                  | 2 +-
 tag/ml-for-code/index.html                     | 2 +-
 "tag/\345\274\200\346\272\220/index.html"      | 2 +-
 tags/index.html                                | 2 +-
 talk/example-talk/index.html                   | 2 +-
 33 files changed, 36 insertions(+), 36 deletions(-)
diff --git a/404.html b/404.html
index 0f11c63..fdc62e9 100644
--- a/404.html
+++ b/404.html
@@ -1,5 +1,5 @@
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 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
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diff --git a/categories/index.html b/categories/index.html
index 7443cf8..9486181 100644
--- a/categories/index.html
+++ b/categories/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
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 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>Categories</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/category/demo/>Demo</a></div><div class="stream-meta article-metadata"><div class=article-metadata><span class=article-date>Dec 13, 2020</span></div></div></div><div class=ml-3></div></div><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/category/%E6%95%99%E7%A8%8B/>教程</a></div><div class="stream-meta article-metadata"><div class=article-metadata><span class=article-date>Dec 13, 2020</span></div></div></div><div class=ml-3></div></div></div></div><div class=page-footer><div class=container><footer class=site-footer><p class="powered-by copyright-license-text">© 2023 Me. This work is licensed under <a href=https://creativecommons.org/licenses/by-nc-nd/4.0 rel="noopener noreferrer" target=_blank>CC BY NC ND 4.0</a></p><p class="powered-by footer-license-icons"><a href=https://creativecommons.org/licenses/by-nc-nd/4.0 rel="noopener noreferrer" target=_blank aria-label="Creative Commons"><i class="fab fa-creative-commons fa-2x" aria-hidden=true></i>
diff --git a/category/demo/index.html b/category/demo/index.html
index a3bbbed..a58c405 100644
--- a/category/demo/index.html
+++ b/category/demo/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
-<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Personal Webpage"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/category/demo/><link rel=canonical href=https://shushanarakelyan.github.io/category/demo/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/category/demo/"><meta property="og:title" content="Demo | Shushan Arakelyan's homepage"><meta property="og:description" content="Personal Webpage"><meta property="og:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:locale" content="en-us"><meta property="og:updated_time" content="2020-12-13T00:00:00+00:00"><link rel=alternate href=/category/demo/index.xml type=application/rss+xml title="Shushan Arakelyan's homepage"><title>Demo | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><script>(function(e,t,n,s,o,i,a){e[n]=e[n]||function(){(e[n].q=e[n].q||[]).push(arguments)},i=t.createElement(s),i.async=1,i.src="https://www.clarity.ms/tag/"+o,a=t.getElementsByTagName(s)[0],a.parentNode.insertBefore(i,a)})(window,document,"clarity","script","k3m4j9k73i")</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Personal Webpage"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/category/demo/><link rel=canonical href=https://shushanarakelyan.github.io/category/demo/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/category/demo/"><meta property="og:title" content="Demo | Shushan Arakelyan's homepage"><meta property="og:description" content="Personal Webpage"><meta property="og:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:locale" content="en-us"><meta property="og:updated_time" content="2020-12-13T00:00:00+00:00"><link rel=alternate href=/category/demo/index.xml type=application/rss+xml title="Shushan Arakelyan's homepage"><title>Demo | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>Demo</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/post/getting-started/>Welcome to Wowchemy, the website builder for Hugo</a></div><a href=/post/getting-started/ class=summary-link><div class=article-style>Welcome 👋 We know that first impressions are important, so we&rsquo;ve populated your new site with some initial content to help you get familiar with everything in no time.</div></a><div class="stream-meta article-metadata"><div class=article-metadata><div><span>admin</span>, <span>吳恩達</span></div><span class=article-date>Dec 13, 2020</span>
diff --git "a/category/\346\225\231\347\250\213/index.html" "b/category/\346\225\231\347\250\213/index.html"
index b986f4f..4e6eedb 100644
--- "a/category/\346\225\231\347\250\213/index.html"
+++ "b/category/\346\225\231\347\250\213/index.html"
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
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+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><script>(function(e,t,n,s,o,i,a){e[n]=e[n]||function(){(e[n].q=e[n].q||[]).push(arguments)},i=t.createElement(s),i.async=1,i.src="https://www.clarity.ms/tag/"+o,a=t.getElementsByTagName(s)[0],a.parentNode.insertBefore(i,a)})(window,document,"clarity","script","k3m4j9k73i")</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Personal Webpage"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/category/%E6%95%99%E7%A8%8B/><link rel=canonical href=https://shushanarakelyan.github.io/category/%E6%95%99%E7%A8%8B/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/category/%E6%95%99%E7%A8%8B/"><meta property="og:title" content="教程 | Shushan Arakelyan's homepage"><meta property="og:description" content="Personal Webpage"><meta property="og:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:locale" content="en-us"><meta property="og:updated_time" content="2020-12-13T00:00:00+00:00"><link rel=alternate href=/category/%E6%95%99%E7%A8%8B/index.xml type=application/rss+xml title="Shushan Arakelyan's homepage"><title>教程 | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>教程</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/post/getting-started/>Welcome to Wowchemy, the website builder for Hugo</a></div><a href=/post/getting-started/ class=summary-link><div class=article-style>Welcome 👋 We know that first impressions are important, so we&rsquo;ve populated your new site with some initial content to help you get familiar with everything in no time.</div></a><div class="stream-meta article-metadata"><div class=article-metadata><div><span>admin</span>, <span>吳恩達</span></div><span class=article-date>Dec 13, 2020</span>
diff --git a/event/index.html b/event/index.html
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+++ b/event/index.html
@@ -1,5 +1,5 @@
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 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>Recent & Upcoming Talks</h1></div><div class=universal-wrapper><div class=row><div class=col-lg-12><div class=row id=talk_list><div class=col-lg-2><h3>2030</h3></div><div class=col-lg-10><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/talk/example-talk/>Example Talk</a></div><a href=/talk/example-talk/ class=summary-link><div class=article-style>An example talk using Wowchemy&rsquo;s Markdown slides feature.</div></a><div class="stream-meta article-metadata"><div><span>Jun 1, 2030 1:00 PM &mdash; 3:00 PM</span>
diff --git a/index.html b/index.html
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+++ b/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
-<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Personal Webpage"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/><link rel=canonical href=https://shushanarakelyan.github.io/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/"><meta property="og:title" content="Shushan Arakelyan's homepage"><meta property="og:description" content="Personal Webpage"><meta property="og:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:locale" content="en-us"><meta property="og:updated_time" content="2023-08-06T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"WebSite","potentialAction":{"@type":"SearchAction","target":"https://shushanarakelyan.github.io/?q={search_term_string}","query-input":"required name=search_term_string"},"url":"https://shushanarakelyan.github.io/"}</script><script src=https://identity.netlify.com/v1/netlify-identity-widget.js></script>
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><script>(function(e,t,n,s,o,i,a){e[n]=e[n]||function(){(e[n].q=e[n].q||[]).push(arguments)},i=t.createElement(s),i.async=1,i.src="https://www.clarity.ms/tag/"+o,a=t.getElementsByTagName(s)[0],a.parentNode.insertBefore(i,a)})(window,document,"clarity","script","k3m4j9k73i")</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Personal Webpage"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/><link rel=canonical href=https://shushanarakelyan.github.io/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/"><meta property="og:title" content="Shushan Arakelyan's homepage"><meta property="og:description" content="Personal Webpage"><meta property="og:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:locale" content="en-us"><meta property="og:updated_time" content="2023-08-06T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"WebSite","potentialAction":{"@type":"SearchAction","target":"https://shushanarakelyan.github.io/?q={search_term_string}","query-input":"required name=search_term_string"},"url":"https://shushanarakelyan.github.io/"}</script><script src=https://identity.netlify.com/v1/netlify-identity-widget.js></script>
 <link rel=alternate href=/index.xml type=application/rss+xml title="Shushan Arakelyan's homepage"><title>Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#navbar-main class=page-wrapper data-wc-page-id=3976528693a0108357f4928017600865><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about data-target=#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured data-target=#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact data-target=#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
diff --git a/index.xml b/index.xml
index b8b5a15..2685136 100644
--- a/index.xml
+++ b/index.xml
@@ -264,7 +264,7 @@ console.log('code block');
 &lt;p>Wowchemy supports the popular &lt;a href="https://plot.ly/" target="_blank" rel="noopener">Plotly&lt;/a> format for interactive charts.&lt;/p>
 &lt;p>Save your Plotly JSON in your page folder, for example &lt;code>line-chart.json&lt;/code>, and then add the &lt;code>{{&amp;lt; chart data=&amp;quot;line-chart&amp;quot; &amp;gt;}}&lt;/code> shortcode where you would like the chart to appear.&lt;/p>
 &lt;p>Demo:&lt;/p>
-&lt;div id="chart-461835279" class="chart">&lt;/div>
+&lt;div id="chart-467291583" class="chart">&lt;/div>
 &lt;script>
 (function() {
 let a = setInterval( function() {
@@ -273,7 +273,7 @@ return;
 }
 clearInterval( a );
 Plotly.d3.json("./line-chart.json", function(chart) {
-Plotly.plot('chart-461835279', chart.data, chart.layout, {responsive: true});
+Plotly.plot('chart-467291583', chart.data, chart.layout, {responsive: true});
 });
 }, 500 );
 })();
diff --git a/post/getting-started/index.html b/post/getting-started/index.html
index d98cd72..0312e37 100644
--- a/post/getting-started/index.html
+++ b/post/getting-started/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
-<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Welcome 👋 We know that first impressions are important, so we've populated your new site with some initial content to help you get familiar with everything in no time."><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/post/getting-started/><link rel=canonical href=https://shushanarakelyan.github.io/post/getting-started/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/post/getting-started/featured.jpg"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/post/getting-started/"><meta property="og:title" content="Welcome to Wowchemy, the website builder for Hugo | Shushan Arakelyan's homepage"><meta property="og:description" content="Welcome 👋 We know that first impressions are important, so we've populated your new site with some initial content to help you get familiar with everything in no time."><meta property="og:image" content="https://shushanarakelyan.github.io/post/getting-started/featured.jpg"><meta property="og:locale" content="en-us"><meta property="article:published_time" content="2020-12-13T00:00:00+00:00"><meta property="article:modified_time" content="2020-12-13T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"BlogPosting","mainEntityOfPage":{"@type":"WebPage","@id":"https://shushanarakelyan.github.io/post/getting-started/"},"headline":"Welcome to Wowchemy, the website builder for Hugo","image":["https://shushanarakelyan.github.io/post/getting-started/featured.jpg"],"datePublished":"2020-12-13T00:00:00Z","dateModified":"2020-12-13T00:00:00Z","author":{"@type":"Person","name":"admin"},"publisher":{"@type":"Organization","name":"Shushan Arakelyan's homepage","logo":{"@type":"ImageObject","url":"https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_192x192_fill_lanczos_center_3.png"}},"description":"Welcome 👋 We know that first impressions are important, so we've populated your new site with some initial content to help you get familiar with everything in no time."}</script><title>Welcome to Wowchemy, the website builder for Hugo | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper data-wc-page-id=279b9966ca9cf3121ce924dca452bb1c><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><script>(function(e,t,n,s,o,i,a){e[n]=e[n]||function(){(e[n].q=e[n].q||[]).push(arguments)},i=t.createElement(s),i.async=1,i.src="https://www.clarity.ms/tag/"+o,a=t.getElementsByTagName(s)[0],a.parentNode.insertBefore(i,a)})(window,document,"clarity","script","k3m4j9k73i")</script><meta name=author content="Shushan Arakelyan"><meta name=description 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aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><article class=article><div class="article-container pt-3"><h1>Welcome to Wowchemy, the website builder for Hugo</h1><p class=page-subtitle>Welcome 👋 We know that first impressions are important, so we&rsquo;ve populated your new site with some initial content to help you get familiar with everything in no time.</p><div class=article-metadata><div><span>admin</span>, <span>吳恩達</span></div><span class=article-date>Dec 13, 2020</span>
diff --git a/post/index.html b/post/index.html
index 32cc16b..e89aaf7 100644
--- a/post/index.html
+++ b/post/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
-<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Personal Webpage"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/post/><link rel=canonical href=https://shushanarakelyan.github.io/post/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/post/"><meta property="og:title" content="Posts | Shushan Arakelyan's homepage"><meta property="og:description" content="Personal Webpage"><meta property="og:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:locale" content="en-us"><meta property="og:updated_time" content="2020-12-13T00:00:00+00:00"><link rel=alternate href=/post/index.xml type=application/rss+xml title="Shushan Arakelyan's homepage"><title>Posts | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper data-wc-page-id=6370009740e1eb2ee0b7974f10ecc91f><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><script>(function(e,t,n,s,o,i,a){e[n]=e[n]||function(){(e[n].q=e[n].q||[]).push(arguments)},i=t.createElement(s),i.async=1,i.src="https://www.clarity.ms/tag/"+o,a=t.getElementsByTagName(s)[0],a.parentNode.insertBefore(i,a)})(window,document,"clarity","script","k3m4j9k73i")</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Personal Webpage"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/post/><link rel=canonical href=https://shushanarakelyan.github.io/post/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/post/"><meta property="og:title" content="Posts | Shushan Arakelyan's homepage"><meta property="og:description" content="Personal Webpage"><meta property="og:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:locale" content="en-us"><meta property="og:updated_time" content="2020-12-13T00:00:00+00:00"><link rel=alternate href=/post/index.xml type=application/rss+xml title="Shushan Arakelyan's homepage"><title>Posts | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper data-wc-page-id=6370009740e1eb2ee0b7974f10ecc91f><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>Posts</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/post/getting-started/>Welcome to Wowchemy, the website builder for Hugo</a></div><a href=/post/getting-started/ class=summary-link><div class=article-style>Welcome 👋 We know that first impressions are important, so we&rsquo;ve populated your new site with some initial content to help you get familiar with everything in no time.</div></a><div class="stream-meta article-metadata"><div class=article-metadata><div><span>admin</span>, <span>吳恩達</span></div><span class=article-date>Dec 13, 2020</span>
diff --git a/post/index.xml b/post/index.xml
index bd8b761..e847e1b 100644
--- a/post/index.xml
+++ b/post/index.xml
@@ -145,7 +145,7 @@ console.log('code block');
 &lt;p>Wowchemy supports the popular &lt;a href="https://plot.ly/" target="_blank" rel="noopener">Plotly&lt;/a> format for interactive charts.&lt;/p>
 &lt;p>Save your Plotly JSON in your page folder, for example &lt;code>line-chart.json&lt;/code>, and then add the &lt;code>{{&amp;lt; chart data=&amp;quot;line-chart&amp;quot; &amp;gt;}}&lt;/code> shortcode where you would like the chart to appear.&lt;/p>
 &lt;p>Demo:&lt;/p>
-&lt;div id="chart-461835279" class="chart">&lt;/div>
+&lt;div id="chart-467291583" class="chart">&lt;/div>
 &lt;script>
 (function() {
 let a = setInterval( function() {
@@ -154,7 +154,7 @@ return;
 }
 clearInterval( a );
 Plotly.d3.json("./line-chart.json", function(chart) {
-Plotly.plot('chart-461835279', chart.data, chart.layout, {responsive: true});
+Plotly.plot('chart-467291583', chart.data, chart.layout, {responsive: true});
 });
 }, 500 );
 })();
diff --git a/post/jupyter/index.html b/post/jupyter/index.html
index aaf97d0..8e762b6 100644
--- a/post/jupyter/index.html
+++ b/post/jupyter/index.html
@@ -1,5 +1,5 @@
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diff --git a/post/writing-technical-content/index.html b/post/writing-technical-content/index.html
index 78bafbe..e2701a3 100644
--- a/post/writing-technical-content/index.html
+++ b/post/writing-technical-content/index.html
@@ -1,7 +1,7 @@
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@@ -69,7 +69,7 @@
       console.log('hello');
       console.log('code block');
       ```
-    - Math: $x = {-b \pm \sqrt{b^2-4ac} \over 2a}$</pre></div><h3 id=charts>Charts</h3><p>Wowchemy supports the popular <a href=https://plot.ly/ target=_blank rel=noopener>Plotly</a> format for interactive charts.</p><p>Save your Plotly JSON in your page folder, for example <code>line-chart.json</code>, and then add the <code>{{&lt; chart data="line-chart" >}}</code> shortcode where you would like the chart to appear.</p><p>Demo:</p><div id=chart-461835279 class=chart></div><script>(function(){let e=setInterval(function(){if(typeof window.Plotly=="undefined")return;clearInterval(e),Plotly.d3.json("./line-chart.json",function(e){Plotly.plot("chart-461835279",e.data,e.layout,{responsive:!0})})},500)})()</script><p>You might also find the <a href=http://plotly-json-editor.getforge.io/ target=_blank rel=noopener>Plotly JSON Editor</a> useful.</p><h3 id=math>Math</h3><p>Wowchemy supports a Markdown extension for $\LaTeX$ math. You can enable this feature by toggling the <code>math</code> option in your <code>config/_default/params.yaml</code> file.</p><p>To render <em>inline</em> or <em>block</em> math, wrap your LaTeX math with <code>{{&lt; math >}}$...${{&lt; /math >}}</code> or <code>{{&lt; math >}}$$...$${{&lt; /math >}}</code>, respectively. (We wrap the LaTeX math in the Wowchemy <em>math</em> shortcode to prevent Hugo rendering our math as Markdown. The <em>math</em> shortcode is new in v5.5-dev.)</p><p>Example <strong>math block</strong>:</p><div class=highlight><pre tabindex=0 class=chroma><code class=language-latex data-lang=latex><span class=line><span class=cl><span class=nb>{{</span>&lt; math &gt;<span class=nb>}}</span>
+    - Math: $x = {-b \pm \sqrt{b^2-4ac} \over 2a}$</pre></div><h3 id=charts>Charts</h3><p>Wowchemy supports the popular <a href=https://plot.ly/ target=_blank rel=noopener>Plotly</a> format for interactive charts.</p><p>Save your Plotly JSON in your page folder, for example <code>line-chart.json</code>, and then add the <code>{{&lt; chart data="line-chart" >}}</code> shortcode where you would like the chart to appear.</p><p>Demo:</p><div id=chart-467291583 class=chart></div><script>(function(){let e=setInterval(function(){if(typeof window.Plotly=="undefined")return;clearInterval(e),Plotly.d3.json("./line-chart.json",function(e){Plotly.plot("chart-467291583",e.data,e.layout,{responsive:!0})})},500)})()</script><p>You might also find the <a href=http://plotly-json-editor.getforge.io/ target=_blank rel=noopener>Plotly JSON Editor</a> useful.</p><h3 id=math>Math</h3><p>Wowchemy supports a Markdown extension for $\LaTeX$ math. You can enable this feature by toggling the <code>math</code> option in your <code>config/_default/params.yaml</code> file.</p><p>To render <em>inline</em> or <em>block</em> math, wrap your LaTeX math with <code>{{&lt; math >}}$...${{&lt; /math >}}</code> or <code>{{&lt; math >}}$$...$${{&lt; /math >}}</code>, respectively. (We wrap the LaTeX math in the Wowchemy <em>math</em> shortcode to prevent Hugo rendering our math as Markdown. The <em>math</em> shortcode is new in v5.5-dev.)</p><p>Example <strong>math block</strong>:</p><div class=highlight><pre tabindex=0 class=chroma><code class=language-latex data-lang=latex><span class=line><span class=cl><span class=nb>{{</span>&lt; math &gt;<span class=nb>}}</span>
 </span></span><span class=line><span class=cl><span class=sb>$$</span><span class=nb>
 </span></span></span><span class=line><span class=cl><span class=nb></span><span class=nv>\gamma</span><span class=nb>_{n} </span><span class=o>=</span><span class=nb> </span><span class=nv>\frac</span><span class=nb>{ </span><span class=nv>\left</span><span class=nb> | </span><span class=nv>\left</span><span class=nb> </span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb> x_{n} </span><span class=o>-</span><span class=nb> </span><span class=nv>\mathbf</span><span class=nb> x_{n</span><span class=o>-</span><span class=m>1</span><span class=nb>} </span><span class=nv>\right</span><span class=nb> </span><span class=o>)</span><span class=nb>^T </span><span class=nv>\left</span><span class=nb> </span><span class=o>[</span><span class=nv>\nabla</span><span class=nb> F </span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb> x_{n}</span><span class=o>)</span><span class=nb> </span><span class=o>-</span><span class=nb> </span><span class=nv>\nabla</span><span class=nb> F </span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb> x_{n</span><span class=o>-</span><span class=m>1</span><span class=nb>}</span><span class=o>)</span><span class=nb> </span><span class=nv>\right</span><span class=nb> </span><span class=o>]</span><span class=nb> </span><span class=nv>\right</span><span class=nb> |}{</span><span class=nv>\left</span><span class=nb> </span><span class=nv>\|\nabla</span><span class=nb> F</span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb>{x}_{n}</span><span class=o>)</span><span class=nb> </span><span class=o>-</span><span class=nb> </span><span class=nv>\nabla</span><span class=nb> F</span><span class=o>(</span><span class=nv>\mathbf</span><span class=nb>{x}_{n</span><span class=o>-</span><span class=m>1</span><span class=nb>}</span><span class=o>)</span><span class=nb> </span><span class=nv>\right</span><span class=nb> </span><span class=nv>\|</span><span class=nb>^</span><span class=m>2</span><span class=nb>}
 </span></span></span><span class=line><span class=cl><span class=nb></span><span class=s>$$</span>
diff --git a/project/example/index.html b/project/example/index.html
index cdb037d..6920a40 100644
--- a/project/example/index.html
+++ b/project/example/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
-<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><meta name=author content="Shushan Arakelyan"><meta name=description content="An example of using the in-built project page."><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/project/example/><link rel=canonical href=https://shushanarakelyan.github.io/project/example/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/project/example/featured.jpg"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/project/example/"><meta property="og:title" content="Example Project | Shushan Arakelyan's homepage"><meta property="og:description" content="An example of using the in-built project page."><meta property="og:image" content="https://shushanarakelyan.github.io/project/example/featured.jpg"><meta property="og:locale" content="en-us"><meta property="article:published_time" content="2016-04-27T00:00:00+00:00"><meta property="article:modified_time" content="2016-04-27T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"Article","mainEntityOfPage":{"@type":"WebPage","@id":"https://shushanarakelyan.github.io/project/example/"},"headline":"Example Project","image":["https://shushanarakelyan.github.io/project/example/featured.jpg"],"datePublished":"2016-04-27T00:00:00Z","dateModified":"2016-04-27T00:00:00Z","author":{"@type":"Person","name":"Shushan Arakelyan"},"publisher":{"@type":"Organization","name":"Shushan Arakelyan's homepage","logo":{"@type":"ImageObject","url":"https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_192x192_fill_lanczos_center_3.png"}},"description":"An example of using the in-built project page."}</script><title>Example Project | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper data-wc-page-id=e8f8d235e8e7f2efd912bfe865363fc3><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
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 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><article class="article article-project"><div class="article-container pt-3"><h1>Example Project</h1><div class=article-metadata><span class=article-date>Apr 27, 2016</span></div><div class="btn-links mb-3"><a class="btn btn-outline-primary btn-page-header" href=https://twitter.com/georgecushen target=_blank rel=noopener><i class="fab fa-twitter mr-1"></i>Follow</a></div></div><div class="article-header article-container featured-image-wrapper mt-4 mb-4" style=max-width:720px;max-height:405px><div style=position:relative><img src=/project/example/featured_hu3d03a01dcc18bc5be0e67db3d8d209a6_224363_720x2500_fit_q75_h2_lanczos.webp width=720 height=405 alt class=featured-image>
diff --git a/project/external-project/index.html b/project/external-project/index.html
index b58cc89..ae9e1b8 100644
--- a/project/external-project/index.html
+++ b/project/external-project/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
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 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><article class="article article-project"><div class="article-container pt-3"><h1>External Project</h1><div class=article-metadata><span class=article-date>Apr 27, 2016</span></div><div class="btn-links mb-3"><a class="btn btn-outline-primary my-1" href=https://example.org target=_blank rel=noopener>Go to Project Site</a></div></div><div class="article-header article-container featured-image-wrapper mt-4 mb-4" style=max-width:720px;max-height:405px><div style=position:relative><img src=/project/external-project/featured_hu3d03a01dcc18bc5be0e67db3d8d209a6_329522_720x2500_fit_q75_h2_lanczos.webp width=720 height=405 alt class=featured-image>
diff --git a/project/index.html b/project/index.html
index 3325e15..1914dea 100644
--- a/project/index.html
+++ b/project/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
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diff --git a/publication-type/1/index.html b/publication-type/1/index.html
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 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
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 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
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 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>1</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/publication/code-transfer/>Exploring Distributional Shifts in Large Language Models for Code Analysis</a></div><a href=/publication/code-transfer/ class=summary-link><div class=article-style>We systematically study the capacity of two large language models for code - CodeT5 and Codex - to generalize to out-of-domain data. In …</div></a><div class="stream-meta article-metadata"><div><span>Shushan Arakelyan</span>, <span>Rocktim Jyoti Das</span>, <span>Yi Mao</span>, <span>Xiang Ren</span></div></div><div class=btn-links><a class="btn btn-outline-primary btn-page-header btn-sm" href=https://arxiv.org/pdf/2303.09128.pdf target=_blank rel=noopener>PDF</a>
diff --git a/publication-type/2/index.html b/publication-type/2/index.html
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@@ -1,5 +1,5 @@
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 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
-<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time consuming task for human analysts. In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicability to a number of downstream tasks. We introduce Bin2vec, a new approach leveraging Graph Convolutional Networks (GCN) along with computational program graphs in order to learn a high dimensional representation of binary executable programs. We demonstrate the versatility of this approach by using our representations to solve two semantically different binary analysis tasks – functional algorithm classification and vulnerability discovery. We compare the proposed approach to our own strong baseline as well as published results, and demonstrate improvement over state-of-the-art methods for both tasks. We evaluated Bin2vec on 49191 binaries for the functional algorithm classification task, and on 30 different CWE-IDs including at least 100 CVE entries each for the vulnerability discovery task. We set a new state-of-the-art result by reducing the classification error by 40\% compared to the source-code based inst2vec approach, while working on binary code. For almost every vulnerability class in our dataset, our prediction accuracy is over 80\% (and over 90\% in multiple classes)."><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/publication/bin2vec/><link rel=canonical href=https://shushanarakelyan.github.io/publication/bin2vec/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/publication/bin2vec/featured.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/publication/bin2vec/"><meta property="og:title" content="Bin2vec: learning representations of binary executable programs for security tasks | Shushan Arakelyan's homepage"><meta property="og:description" content="Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time consuming task for human analysts. In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicability to a number of downstream tasks. We introduce Bin2vec, a new approach leveraging Graph Convolutional Networks (GCN) along with computational program graphs in order to learn a high dimensional representation of binary executable programs. We demonstrate the versatility of this approach by using our representations to solve two semantically different binary analysis tasks – functional algorithm classification and vulnerability discovery. We compare the proposed approach to our own strong baseline as well as published results, and demonstrate improvement over state-of-the-art methods for both tasks. We evaluated Bin2vec on 49191 binaries for the functional algorithm classification task, and on 30 different CWE-IDs including at least 100 CVE entries each for the vulnerability discovery task. We set a new state-of-the-art result by reducing the classification error by 40\% compared to the source-code based inst2vec approach, while working on binary code. For almost every vulnerability class in our dataset, our prediction accuracy is over 80\% (and over 90\% in multiple classes)."><meta property="og:image" content="https://shushanarakelyan.github.io/publication/bin2vec/featured.png"><meta property="og:locale" content="en-us"><meta property="article:published_time" content="2021-05-01T00:00:00+00:00"><meta property="article:modified_time" content="2021-05-01T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"Article","mainEntityOfPage":{"@type":"WebPage","@id":"https://shushanarakelyan.github.io/publication/bin2vec/"},"headline":"Bin2vec: learning representations of binary executable programs for security tasks","image":["https://shushanarakelyan.github.io/publication/bin2vec/featured.png"],"datePublished":"2021-05-01T00:00:00Z","dateModified":"2021-05-01T00:00:00Z","author":{"@type":"Person","name":"Shushan Arakelyan"},"publisher":{"@type":"Organization","name":"Shushan Arakelyan's homepage","logo":{"@type":"ImageObject","url":"https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_192x192_fill_lanczos_center_3.png"}},"description":"Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time consuming task for human analysts. In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicability to a number of downstream tasks. We introduce Bin2vec, a new approach leveraging Graph Convolutional Networks (GCN) along with computational program graphs in order to learn a high dimensional representation of binary executable programs. We demonstrate the versatility of this approach by using our representations to solve two semantically different binary analysis tasks – functional algorithm classification and vulnerability discovery. We compare the proposed approach to our own strong baseline as well as published results, and demonstrate improvement over state-of-the-art methods for both tasks. We evaluated Bin2vec on 49191 binaries for the functional algorithm classification task, and on 30 different CWE-IDs including at least 100 CVE entries each for the vulnerability discovery task. We set a new state-of-the-art result by reducing the classification error by 40\\% compared to the source-code based inst2vec approach, while working on binary code. 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In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicability to a number of downstream tasks. We introduce Bin2vec, a new approach leveraging Graph Convolutional Networks (GCN) along with computational program graphs in order to learn a high dimensional representation of binary executable programs. We demonstrate the versatility of this approach by using our representations to solve two semantically different binary analysis tasks – functional algorithm classification and vulnerability discovery. We compare the proposed approach to our own strong baseline as well as published results, and demonstrate improvement over state-of-the-art methods for both tasks. We evaluated Bin2vec on 49191 binaries for the functional algorithm classification task, and on 30 different CWE-IDs including at least 100 CVE entries each for the vulnerability discovery task. We set a new state-of-the-art result by reducing the classification error by 40\% compared to the source-code based inst2vec approach, while working on binary code. For almost every vulnerability class in our dataset, our prediction accuracy is over 80\% (and over 90\% in multiple classes)."><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/publication/bin2vec/><link rel=canonical href=https://shushanarakelyan.github.io/publication/bin2vec/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/publication/bin2vec/featured.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/publication/bin2vec/"><meta property="og:title" content="Bin2vec: learning representations of binary executable programs for security tasks | Shushan Arakelyan's homepage"><meta property="og:description" content="Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time consuming task for human analysts. In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicability to a number of downstream tasks. We introduce Bin2vec, a new approach leveraging Graph Convolutional Networks (GCN) along with computational program graphs in order to learn a high dimensional representation of binary executable programs. We demonstrate the versatility of this approach by using our representations to solve two semantically different binary analysis tasks – functional algorithm classification and vulnerability discovery. We compare the proposed approach to our own strong baseline as well as published results, and demonstrate improvement over state-of-the-art methods for both tasks. We evaluated Bin2vec on 49191 binaries for the functional algorithm classification task, and on 30 different CWE-IDs including at least 100 CVE entries each for the vulnerability discovery task. We set a new state-of-the-art result by reducing the classification error by 40\% compared to the source-code based inst2vec approach, while working on binary code. For almost every vulnerability class in our dataset, our prediction accuracy is over 80\% (and over 90\% in multiple classes)."><meta property="og:image" content="https://shushanarakelyan.github.io/publication/bin2vec/featured.png"><meta property="og:locale" content="en-us"><meta property="article:published_time" content="2021-05-01T00:00:00+00:00"><meta property="article:modified_time" content="2021-05-01T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"Article","mainEntityOfPage":{"@type":"WebPage","@id":"https://shushanarakelyan.github.io/publication/bin2vec/"},"headline":"Bin2vec: learning representations of binary executable programs for security tasks","image":["https://shushanarakelyan.github.io/publication/bin2vec/featured.png"],"datePublished":"2021-05-01T00:00:00Z","dateModified":"2021-05-01T00:00:00Z","author":{"@type":"Person","name":"Shushan Arakelyan"},"publisher":{"@type":"Organization","name":"Shushan Arakelyan's homepage","logo":{"@type":"ImageObject","url":"https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_192x192_fill_lanczos_center_3.png"}},"description":"Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time consuming task for human analysts. In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicability to a number of downstream tasks. We introduce Bin2vec, a new approach leveraging Graph Convolutional Networks (GCN) along with computational program graphs in order to learn a high dimensional representation of binary executable programs. We demonstrate the versatility of this approach by using our representations to solve two semantically different binary analysis tasks – functional algorithm classification and vulnerability discovery. We compare the proposed approach to our own strong baseline as well as published results, and demonstrate improvement over state-of-the-art methods for both tasks. We evaluated Bin2vec on 49191 binaries for the functional algorithm classification task, and on 30 different CWE-IDs including at least 100 CVE entries each for the vulnerability discovery task. We set a new state-of-the-art result by reducing the classification error by 40\\% compared to the source-code based inst2vec approach, while working on binary code. For almost every vulnerability class in our dataset, our prediction accuracy is over 80\\% (and over 90\\% in multiple classes)."}</script><title>Bin2vec: learning representations of binary executable programs for security tasks | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper data-wc-page-id=2e71e0be373de3bef7f7940b87809e78><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
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 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class=pub><div class="article-container pt-3"><h1>Bin2vec: learning representations of binary executable programs for security tasks</h1><div class=article-metadata><div><span>Shushan Arakelyan</span>, <span>Sima Arasteh</span>, <span>Christophe Hauser</span>, <span>Erik Kline</span>, <span>Aram Galstyan</span></div><span class=article-date>May, 2021</span></div><div class="btn-links mb-3"><a class="btn btn-outline-primary btn-page-header" href=https://cybersecurity.springeropen.com/articles/10.1186/s42400-021-00088-4 target=_blank rel=noopener>PDF</a>
diff --git a/publication/code-transfer/index.html b/publication/code-transfer/index.html
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 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
-<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><meta name=author content="Shushan Arakelyan"><meta name=description content="We systematically study the capacity of two large language models for code - CodeT5 and Codex - to generalize to out-of-domain data. In this study, we consider two fundamental applications - code summarization, and code generation. We split data into domains following its natural boundaries - by an organization, by a project, and by a module within the software project. This makes recognition of in-domain vs out-of-domain data at the time of deployment trivial. We establish that samples from each new domain present both models with a significant challenge of distribution shift. We study how well different established methods can adapt models to better generalize to new domains. Our experiments show that while multitask learning alone is a reasonable baseline, combining it with few-shot finetuning on examples retrieved from training data can achieve very strong performance. In fact, according to our experiments, this solution can outperform direct finetuning for very low-data scenarios. Finally, we consider variations of this approach to create a more broadly applicable method to adapt to multiple domains at once. We find that in the case of code generation, a model adapted to multiple domains simultaneously performs on par with those adapted to each domain individually"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/publication/code-transfer/><link rel=canonical href=https://shushanarakelyan.github.io/publication/code-transfer/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/publication/code-transfer/featured.gif"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/publication/code-transfer/"><meta property="og:title" content="Exploring Distributional Shifts in Large Language Models for Code Analysis | Shushan Arakelyan's homepage"><meta property="og:description" content="We systematically study the capacity of two large language models for code - CodeT5 and Codex - to generalize to out-of-domain data. In this study, we consider two fundamental applications - code summarization, and code generation. We split data into domains following its natural boundaries - by an organization, by a project, and by a module within the software project. This makes recognition of in-domain vs out-of-domain data at the time of deployment trivial. We establish that samples from each new domain present both models with a significant challenge of distribution shift. We study how well different established methods can adapt models to better generalize to new domains. Our experiments show that while multitask learning alone is a reasonable baseline, combining it with few-shot finetuning on examples retrieved from training data can achieve very strong performance. In fact, according to our experiments, this solution can outperform direct finetuning for very low-data scenarios. Finally, we consider variations of this approach to create a more broadly applicable method to adapt to multiple domains at once. We find that in the case of code generation, a model adapted to multiple domains simultaneously performs on par with those adapted to each domain individually"><meta property="og:image" content="https://shushanarakelyan.github.io/publication/code-transfer/featured.gif"><meta property="og:locale" content="en-us"><meta property="article:published_time" content="2023-03-15T00:00:00+00:00"><meta property="article:modified_time" content="2023-03-15T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"Article","mainEntityOfPage":{"@type":"WebPage","@id":"https://shushanarakelyan.github.io/publication/code-transfer/"},"headline":"Exploring Distributional Shifts in Large Language Models for Code Analysis","image":["https://shushanarakelyan.github.io/publication/code-transfer/featured.gif"],"datePublished":"2023-03-15T00:00:00Z","dateModified":"2023-03-15T00:00:00Z","author":{"@type":"Person","name":"Shushan Arakelyan"},"publisher":{"@type":"Organization","name":"Shushan Arakelyan's homepage","logo":{"@type":"ImageObject","url":"https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_192x192_fill_lanczos_center_3.png"}},"description":"We systematically study the capacity of two large language models for code - CodeT5 and Codex - to generalize to out-of-domain data. 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We find that in the case of code generation, a model adapted to multiple domains simultaneously performs on par with those adapted to each domain individually"}</script><title>Exploring Distributional Shifts in Large Language Models for Code Analysis | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper data-wc-page-id=269dfd064b42d2e5c7ab497e1c36e728><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><script>(function(e,t,n,s,o,i,a){e[n]=e[n]||function(){(e[n].q=e[n].q||[]).push(arguments)},i=t.createElement(s),i.async=1,i.src="https://www.clarity.ms/tag/"+o,a=t.getElementsByTagName(s)[0],a.parentNode.insertBefore(i,a)})(window,document,"clarity","script","k3m4j9k73i")</script><meta name=author content="Shushan Arakelyan"><meta name=description content="We systematically study the capacity of two large language models for code - CodeT5 and Codex - to generalize to out-of-domain data. In this study, we consider two fundamental applications - code summarization, and code generation. We split data into domains following its natural boundaries - by an organization, by a project, and by a module within the software project. This makes recognition of in-domain vs out-of-domain data at the time of deployment trivial. We establish that samples from each new domain present both models with a significant challenge of distribution shift. We study how well different established methods can adapt models to better generalize to new domains. Our experiments show that while multitask learning alone is a reasonable baseline, combining it with few-shot finetuning on examples retrieved from training data can achieve very strong performance. In fact, according to our experiments, this solution can outperform direct finetuning for very low-data scenarios. Finally, we consider variations of this approach to create a more broadly applicable method to adapt to multiple domains at once. We find that in the case of code generation, a model adapted to multiple domains simultaneously performs on par with those adapted to each domain individually"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/publication/code-transfer/><link rel=canonical href=https://shushanarakelyan.github.io/publication/code-transfer/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/publication/code-transfer/featured.gif"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/publication/code-transfer/"><meta property="og:title" content="Exploring Distributional Shifts in Large Language Models for Code Analysis | Shushan Arakelyan's homepage"><meta property="og:description" content="We systematically study the capacity of two large language models for code - CodeT5 and Codex - to generalize to out-of-domain data. In this study, we consider two fundamental applications - code summarization, and code generation. We split data into domains following its natural boundaries - by an organization, by a project, and by a module within the software project. This makes recognition of in-domain vs out-of-domain data at the time of deployment trivial. We establish that samples from each new domain present both models with a significant challenge of distribution shift. We study how well different established methods can adapt models to better generalize to new domains. Our experiments show that while multitask learning alone is a reasonable baseline, combining it with few-shot finetuning on examples retrieved from training data can achieve very strong performance. In fact, according to our experiments, this solution can outperform direct finetuning for very low-data scenarios. Finally, we consider variations of this approach to create a more broadly applicable method to adapt to multiple domains at once. We find that in the case of code generation, a model adapted to multiple domains simultaneously performs on par with those adapted to each domain individually"><meta property="og:image" content="https://shushanarakelyan.github.io/publication/code-transfer/featured.gif"><meta property="og:locale" content="en-us"><meta property="article:published_time" content="2023-03-15T00:00:00+00:00"><meta property="article:modified_time" content="2023-03-15T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"Article","mainEntityOfPage":{"@type":"WebPage","@id":"https://shushanarakelyan.github.io/publication/code-transfer/"},"headline":"Exploring Distributional Shifts in Large Language Models for Code Analysis","image":["https://shushanarakelyan.github.io/publication/code-transfer/featured.gif"],"datePublished":"2023-03-15T00:00:00Z","dateModified":"2023-03-15T00:00:00Z","author":{"@type":"Person","name":"Shushan Arakelyan"},"publisher":{"@type":"Organization","name":"Shushan Arakelyan's homepage","logo":{"@type":"ImageObject","url":"https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_192x192_fill_lanczos_center_3.png"}},"description":"We systematically study the capacity of two large language models for code - CodeT5 and Codex - to generalize to out-of-domain data. In this study, we consider two fundamental applications - code summarization, and code generation. We split data into domains following its natural boundaries - by an organization, by a project, and by a module within the software project. This makes recognition of in-domain vs out-of-domain data at the time of deployment trivial. We establish that samples from each new domain present both models with a significant challenge of distribution shift. We study how well different established methods can adapt models to better generalize to new domains. Our experiments show that while multitask learning alone is a reasonable baseline, combining it with few-shot finetuning on examples retrieved from training data can achieve very strong performance. In fact, according to our experiments, this solution can outperform direct finetuning for very low-data scenarios. Finally, we consider variations of this approach to create a more broadly applicable method to adapt to multiple domains at once. We find that in the case of code generation, a model adapted to multiple domains simultaneously performs on par with those adapted to each domain individually"}</script><title>Exploring Distributional Shifts in Large Language Models for Code Analysis | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper data-wc-page-id=269dfd064b42d2e5c7ab497e1c36e728><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
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 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class=pub><div class="article-container pt-3"><h1>Exploring Distributional Shifts in Large Language Models for Code Analysis</h1><div class=article-metadata><div><span>Shushan Arakelyan</span>, <span>Rocktim Jyoti Das</span>, <span>Yi Mao</span>, <span>Xiang Ren</span></div><span class=article-date>March, 2023</span></div><div class="btn-links mb-3"><a class="btn btn-outline-primary btn-page-header" href=https://arxiv.org/pdf/2303.09128.pdf target=_blank rel=noopener>PDF</a>
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diff --git a/publication/ns3/index.html b/publication/ns3/index.html
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+++ b/publication/ns3/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
-<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Semantic code search is the task of retrieving a code snippet given a textual description of its functionality. Recent work has been focused on using similarity metrics between neural embeddings of text and code. However, current language models are known to struggle with longer, compositional sentences, and multi-step reasoning. To overcome this limitation, we propose supplementing the query sentence with a layout of its semantic structure. The semantic layout is used to break down the final reasoning decision into a series of lower-level decisions. We use a Neural Module Network architecture to implement this idea. We compare our model - *NS3* (Neuro-Symbolic Semantic Search)-to a number of baselines, including state-of-the-art semantic code retrieval methods, such as CodeBERT, CuBERT and GraphCodeBERT, and evaluate on two datasets-Code Search Net (CSN) and Code Search and Question Answering (CoSQA). On these datasets, we demonstrate that our approach results in higher performance. We also perform additional studies to show the effectiveness of our modular design when handling compositional queries."><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/publication/ns3/><link rel=canonical href=https://shushanarakelyan.github.io/publication/ns3/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/publication/ns3/featured.jpg"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/publication/ns3/"><meta property="og:title" content="NS3: Neuro-symbolic Semantic Code Search | Shushan Arakelyan's homepage"><meta property="og:description" content="Semantic code search is the task of retrieving a code snippet given a textual description of its functionality. Recent work has been focused on using similarity metrics between neural embeddings of text and code. However, current language models are known to struggle with longer, compositional sentences, and multi-step reasoning. To overcome this limitation, we propose supplementing the query sentence with a layout of its semantic structure. The semantic layout is used to break down the final reasoning decision into a series of lower-level decisions. We use a Neural Module Network architecture to implement this idea. We compare our model - *NS3* (Neuro-Symbolic Semantic Search)-to a number of baselines, including state-of-the-art semantic code retrieval methods, such as CodeBERT, CuBERT and GraphCodeBERT, and evaluate on two datasets-Code Search Net (CSN) and Code Search and Question Answering (CoSQA). On these datasets, we demonstrate that our approach results in higher performance. We also perform additional studies to show the effectiveness of our modular design when handling compositional queries."><meta property="og:image" content="https://shushanarakelyan.github.io/publication/ns3/featured.jpg"><meta property="og:locale" content="en-us"><meta property="article:published_time" content="2022-12-01T00:00:00+00:00"><meta property="article:modified_time" content="2022-12-01T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"Article","mainEntityOfPage":{"@type":"WebPage","@id":"https://shushanarakelyan.github.io/publication/ns3/"},"headline":"NS3: Neuro-symbolic Semantic Code Search","image":["https://shushanarakelyan.github.io/publication/ns3/featured.jpg"],"datePublished":"2022-12-01T00:00:00Z","dateModified":"2022-12-01T00:00:00Z","author":{"@type":"Person","name":"Shushan Arakelyan"},"publisher":{"@type":"Organization","name":"Shushan Arakelyan's homepage","logo":{"@type":"ImageObject","url":"https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_192x192_fill_lanczos_center_3.png"}},"description":"Semantic code search is the task of retrieving a code snippet given a textual description of its functionality. 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We also perform additional studies to show the effectiveness of our modular design when handling compositional queries."><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/publication/ns3/><link rel=canonical href=https://shushanarakelyan.github.io/publication/ns3/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary_large_image"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/publication/ns3/featured.jpg"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/publication/ns3/"><meta property="og:title" content="NS3: Neuro-symbolic Semantic Code Search | Shushan Arakelyan's homepage"><meta property="og:description" content="Semantic code search is the task of retrieving a code snippet given a textual description of its functionality. Recent work has been focused on using similarity metrics between neural embeddings of text and code. However, current language models are known to struggle with longer, compositional sentences, and multi-step reasoning. To overcome this limitation, we propose supplementing the query sentence with a layout of its semantic structure. The semantic layout is used to break down the final reasoning decision into a series of lower-level decisions. We use a Neural Module Network architecture to implement this idea. We compare our model - *NS3* (Neuro-Symbolic Semantic Search)-to a number of baselines, including state-of-the-art semantic code retrieval methods, such as CodeBERT, CuBERT and GraphCodeBERT, and evaluate on two datasets-Code Search Net (CSN) and Code Search and Question Answering (CoSQA). On these datasets, we demonstrate that our approach results in higher performance. We also perform additional studies to show the effectiveness of our modular design when handling compositional queries."><meta property="og:image" content="https://shushanarakelyan.github.io/publication/ns3/featured.jpg"><meta property="og:locale" content="en-us"><meta property="article:published_time" content="2022-12-01T00:00:00+00:00"><meta property="article:modified_time" content="2022-12-01T00:00:00+00:00"><script type=application/ld+json>{"@context":"https://schema.org","@type":"Article","mainEntityOfPage":{"@type":"WebPage","@id":"https://shushanarakelyan.github.io/publication/ns3/"},"headline":"NS3: Neuro-symbolic Semantic Code Search","image":["https://shushanarakelyan.github.io/publication/ns3/featured.jpg"],"datePublished":"2022-12-01T00:00:00Z","dateModified":"2022-12-01T00:00:00Z","author":{"@type":"Person","name":"Shushan Arakelyan"},"publisher":{"@type":"Organization","name":"Shushan Arakelyan's homepage","logo":{"@type":"ImageObject","url":"https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_192x192_fill_lanczos_center_3.png"}},"description":"Semantic code search is the task of retrieving a code snippet given a textual description of its functionality. Recent work has been focused on using similarity metrics between neural embeddings of text and code. However, current language models are known to struggle with longer, compositional sentences, and multi-step reasoning. To overcome this limitation, we propose supplementing the query sentence with a layout of its semantic structure. The semantic layout is used to break down the final reasoning decision into a series of lower-level decisions. We use a Neural Module Network architecture to implement this idea. We compare our model - *NS3* (Neuro-Symbolic Semantic Search)-to a number of baselines, including state-of-the-art semantic code retrieval methods, such as CodeBERT, CuBERT and GraphCodeBERT, and evaluate on two datasets-Code Search Net (CSN) and Code Search and Question Answering (CoSQA). On these datasets, we demonstrate that our approach results in higher performance. We also perform additional studies to show the effectiveness of our modular design when handling compositional queries."}</script><title>NS3: Neuro-symbolic Semantic Code Search | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper data-wc-page-id=c0ed6b46b9e236d9d225db9cafcbca1a><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
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diff --git a/publication_types/index.html b/publication_types/index.html
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diff --git a/tag/binary-analysis/index.html b/tag/binary-analysis/index.html
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 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>binary analysis</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/publication/bin2vec/>Bin2vec: learning representations of binary executable programs for security tasks</a></div><a href=/publication/bin2vec/ class=summary-link><div class=article-style>Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time …</div></a><div class="stream-meta article-metadata"><div><span>Shushan Arakelyan</span>, <span>Sima Arasteh</span>, <span>Christophe Hauser</span>, <span>Erik Kline</span>, <span>Aram Galstyan</span></div></div><div class=btn-links><a class="btn btn-outline-primary btn-page-header btn-sm" href=https://cybersecurity.springeropen.com/articles/10.1186/s42400-021-00088-4 target=_blank rel=noopener>PDF</a>
diff --git a/tag/binary-code-representation/index.html b/tag/binary-code-representation/index.html
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@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
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 <span><i class="fas fa-bars"></i></span></button><div class="navbar-brand-mobile-wrapper d-inline-flex d-lg-none"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><div class="navbar-collapse main-menu-item collapse justify-content-start" id=navbar-content><ul class="navbar-nav d-md-inline-flex"><li class=nav-item><a class=nav-link href=/#about><span>Home</span></a></li><li class=nav-item><a class=nav-link href=/#featured><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=/#contact><span>Contact</span></a></li><li class=nav-item><a class=nav-link href=/uploads/resume.pdf><span>CV</span></a></li></ul></div><ul class="nav-icons navbar-nav flex-row ml-auto d-flex pl-md-2"><li class="nav-item d-none d-lg-inline-flex"><a class=nav-link href=https://twitter.com/sharakelyan data-toggle=tooltip data-placement=bottom title="Follow me on Twitter" target=_blank rel=noopener aria-label="Follow me on Twitter"><i class="fab fa-twitter" aria-hidden=true></i></a></li><li class=nav-item><a class="nav-link js-search" href=# aria-label=Search><i class="fas fa-search" aria-hidden=true></i></a></li><li class="nav-item dropdown theme-dropdown"><a href=# class=nav-link data-toggle=dropdown aria-haspopup=true aria-label="Display preferences"><i class="fas fa-moon" aria-hidden=true></i></a><div class=dropdown-menu><a href=# class="dropdown-item js-set-theme-light"><span>Light</span></a>
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 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>binary code representation</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/publication/bin2vec/>Bin2vec: learning representations of binary executable programs for security tasks</a></div><a href=/publication/bin2vec/ class=summary-link><div class=article-style>Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time …</div></a><div class="stream-meta article-metadata"><div><span>Shushan Arakelyan</span>, <span>Sima Arasteh</span>, <span>Christophe Hauser</span>, <span>Erik Kline</span>, <span>Aram Galstyan</span></div></div><div class=btn-links><a class="btn btn-outline-primary btn-page-header btn-sm" href=https://cybersecurity.springeropen.com/articles/10.1186/s42400-021-00088-4 target=_blank rel=noopener>PDF</a>
diff --git a/tag/deep-learning/index.html b/tag/deep-learning/index.html
index 5efc7c6..16e5453 100644
--- a/tag/deep-learning/index.html
+++ b/tag/deep-learning/index.html
@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
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+<script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}function trackOutboundLink(e,t){gtag("event","click",{event_category:"outbound",event_label:e,transport_type:"beacon",event_callback:function(){t!=="_blank"&&(document.location=e)}}),console.debug("Outbound link clicked: "+e)}function onClickCallback(e){if(e.target.tagName!=="A"||e.target.host===window.location.host)return;trackOutboundLink(e.target,e.target.getAttribute("target"))}gtag("js",new Date),gtag("config","G-4RG2NC82TZ",{}),gtag("set",{cookie_flags:"SameSite=None;Secure"}),document.addEventListener("click",onClickCallback,!1)</script><script>(function(e,t,n,s,o,i,a){e[n]=e[n]||function(){(e[n].q=e[n].q||[]).push(arguments)},i=t.createElement(s),i.async=1,i.src="https://www.clarity.ms/tag/"+o,a=t.getElementsByTagName(s)[0],a.parentNode.insertBefore(i,a)})(window,document,"clarity","script","k3m4j9k73i")</script><meta name=author content="Shushan Arakelyan"><meta name=description content="Personal Webpage"><link rel=alternate hreflang=en-us href=https://shushanarakelyan.github.io/tag/deep-learning/><link rel=canonical href=https://shushanarakelyan.github.io/tag/deep-learning/><link rel=manifest href=/manifest.webmanifest><link rel=icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_32x32_fill_lanczos_center_3.png><link rel=apple-touch-icon type=image/png href=/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_180x180_fill_lanczos_center_3.png><meta name=theme-color content="#1565c0"><meta property="twitter:card" content="summary"><meta property="twitter:site" content="@ShArakelyan"><meta property="twitter:creator" content="@ShArakelyan"><meta property="twitter:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:site_name" content="Shushan Arakelyan's homepage"><meta property="og:url" content="https://shushanarakelyan.github.io/tag/deep-learning/"><meta property="og:title" content="Deep Learning | Shushan Arakelyan's homepage"><meta property="og:description" content="Personal Webpage"><meta property="og:image" content="https://shushanarakelyan.github.io/media/icon_hub1df45c02ce653505e0d325c1b0f11cf_184863_512x512_fill_lanczos_center_3.png"><meta property="og:locale" content="en-us"><meta property="og:updated_time" content="2016-04-27T00:00:00+00:00"><link rel=alternate href=/tag/deep-learning/index.xml type=application/rss+xml title="Shushan Arakelyan's homepage"><title>Deep Learning | Shushan Arakelyan's homepage</title></head><body id=top data-spy=scroll data-offset=70 data-target=#TableOfContents class=page-wrapper><script src=/js/wowchemy-init.min.ec9d49ca50e4b80bdb08f0417a28ed84.js></script><aside class=search-modal id=search><div class=container><section class=search-header><div class="row no-gutters justify-content-between mb-3"><div class=col-6><h1>Search</h1></div><div class="col-6 col-search-close"><a class=js-search href=# aria-label=Close><i class="fas fa-times-circle text-muted" aria-hidden=true></i></a></div></div><div id=search-box><input name=q id=search-query placeholder=Search... autocapitalize=off autocomplete=off autocorrect=off spellcheck=false type=search class=form-control aria-label=Search...></div></section><section class=section-search-results><div id=search-hits></div></section></div></aside><div class="page-header header--fixed"><header><nav class="navbar navbar-expand-lg navbar-light compensate-for-scrollbar" id=navbar-main><div class=container-xl><div class="d-none d-lg-inline-flex"><a class=navbar-brand href=/>Shushan Arakelyan's homepage</a></div><button type=button class=navbar-toggler data-toggle=collapse data-target=#navbar-content aria-controls=navbar-content aria-expanded=false aria-label="Toggle navigation">
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 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>Deep Learning</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/project/example/>Example Project</a></div><a href=/project/example/ class=summary-link><div class=article-style>An example of using the in-built project page.</div></a><div class="stream-meta article-metadata"></div><div class=btn-links><a class="btn btn-outline-primary btn-page-header btn-sm" href=https://twitter.com/georgecushen target=_blank rel=noopener><i class="fab fa-twitter mr-1"></i>Follow</a></div></div><div class=ml-3><a href=/project/example/><img src=/project/example/featured_hu3d03a01dcc18bc5be0e67db3d8d209a6_224363_150x0_resize_q75_h2_lanczos.webp height=84 width=150 alt="Example Project" loading=lazy></a></div></div></div></div><div class=page-footer><div class=container><footer class=site-footer><p class="powered-by copyright-license-text">© 2023 Me. This work is licensed under <a href=https://creativecommons.org/licenses/by-nc-nd/4.0 rel="noopener noreferrer" target=_blank>CC BY NC ND 4.0</a></p><p class="powered-by footer-license-icons"><a href=https://creativecommons.org/licenses/by-nc-nd/4.0 rel="noopener noreferrer" target=_blank aria-label="Creative Commons"><i class="fab fa-creative-commons fa-2x" aria-hidden=true></i>
diff --git a/tag/demo/index.html b/tag/demo/index.html
index 052d606..fc775c0 100644
--- a/tag/demo/index.html
+++ b/tag/demo/index.html
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 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
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diff --git a/tag/generalizable-models-for-code/index.html b/tag/generalizable-models-for-code/index.html
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@@ -1,5 +1,5 @@
 <!doctype html><!-- This site was created with Wowchemy. https://www.wowchemy.com --><!-- Last Published: December 10, 2023 --><html lang=en-us><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><meta http-equiv=x-ua-compatible content="IE=edge"><meta name=generator content="Wowchemy 5.7.0 for Hugo"><link rel=preconnect href=https://fonts.gstatic.com crossorigin><link rel=preload as=style href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap"><link rel=stylesheet href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&family=Roboto+Mono&family=Roboto:wght@400;700&display=swap" media=print onload='this.media="all"'><link rel=stylesheet href=/css/vendor-bundle.min.047268c6dd09ad74ba54a0ba71837064.css media=print onload='this.media="all"'><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/academicons@1.9.2/css/academicons.min.css integrity="sha512-KlJCpRsLf+KKu2VQa5vmRuClRFjxc5lXO03ixZt82HZUk41+1I0bD8KBSA0fY290ayMfWYI9udIqeOWSu1/uZg==" crossorigin=anonymous media=print onload='this.media="all"'><link rel=stylesheet href=/css/wowchemy.042e26407c9e383d96a1f26d6787c686.css><link rel=stylesheet href=/css/libs/chroma/github-light.min.css title=hl-light media=print onload='this.media="all"'><link rel=stylesheet href=/css/libs/chroma/dracula.min.css title=hl-dark media=print onload='this.media="all"' disabled><script async src="https://www.googletagmanager.com/gtag/js?id=G-4RG2NC82TZ"></script>
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 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>Generalizable Models for Code</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/publication/ns3/>NS3: Neuro-symbolic Semantic Code Search</a></div><a href=/publication/ns3/ class=summary-link><div class=article-style>Semantic code search is the task of retrieving a code snippet given a textual description of its functionality. Recent work has been …</div></a><div class="stream-meta article-metadata"><div><span>Shushan Arakelyan</span>, <span>Anna Hakhverdyan</span>, <span>Miltiadis Allamanis</span>, <span>Luis Garcia</span>, <span>Christophe Hauser</span>, <span>Xiang Ren</span></div></div><div class=btn-links><a class="btn btn-outline-primary btn-page-header btn-sm" href=https://proceedings.neurips.cc/paper_files/paper/2022/hash/43f5f6c5cb333115914c8448b8506411-Abstract-Conference.html target=_blank rel=noopener>PDF</a>
diff --git a/tag/generelization/index.html b/tag/generelization/index.html
index 6a2580f..4566c0d 100644
--- a/tag/generelization/index.html
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diff --git a/tag/ml-for-code/index.html b/tag/ml-for-code/index.html
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diff --git "a/tag/\345\274\200\346\272\220/index.html" "b/tag/\345\274\200\346\272\220/index.html"
index 4af22ab..d68e084 100644
--- "a/tag/\345\274\200\346\272\220/index.html"
+++ "b/tag/\345\274\200\346\272\220/index.html"
@@ -1,5 +1,5 @@
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 <a href=# class="dropdown-item js-set-theme-dark"><span>Dark</span></a>
 <a href=# class="dropdown-item js-set-theme-auto"><span>Automatic</span></a></div></li></ul></div></nav></header></div><div class=page-body><div class="universal-wrapper pt-3"><h1>开源</h1></div><div class=universal-wrapper><div class="media stream-item view-compact"><div class=media-body><div class="section-subheading article-title mb-0 mt-0"><a href=/post/getting-started/>Welcome to Wowchemy, the website builder for Hugo</a></div><a href=/post/getting-started/ class=summary-link><div class=article-style>Welcome 👋 We know that first impressions are important, so we&rsquo;ve populated your new site with some initial content to help you get familiar with everything in no time.</div></a><div class="stream-meta article-metadata"><div class=article-metadata><div><span>admin</span>, <span>吳恩達</span></div><span class=article-date>Dec 13, 2020</span>
diff --git a/tags/index.html b/tags/index.html
index e173cd5..50e3950 100644
--- a/tags/index.html
+++ b/tags/index.html
@@ -1,5 +1,5 @@
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diff --git a/talk/example-talk/index.html b/talk/example-talk/index.html
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+++ b/talk/example-talk/index.html
@@ -1,5 +1,5 @@
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