[2102.05918] Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

<?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"> <head> <title>[2102.05918] Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision</title> <meta name="viewport" content="width=device-width, initial-scale=1"> <link rel="apple-touch-icon" sizes="180x180" href="/static/browse/0.3.4/images/icons/apple-touch-icon.png"> <link rel="icon" type="image/png" sizes="32x32" href="/static/browse/0.3.4/images/icons/favicon-32x32.png"> <link rel="icon" type="image/png" sizes="16x16" href="/static/browse/0.3.4/images/icons/favicon-16x16.png"> <link rel="manifest" href="/static/browse/0.3.4/images/icons/site.webmanifest"> <link rel="mask-icon" href="/static/browse/0.3.4/images/icons/safari-pinned-tab.svg" color="#5bbad5"> <meta name="msapplication-TileColor" content="#da532c"> <meta name="theme-color" content="#ffffff"> <link rel="stylesheet" type="text/css" media="screen" href="/static/browse/0.3.4/css/arXiv.css?v=20240822" /> <link rel="stylesheet" type="text/css" media="print" href="/static/browse/0.3.4/css/arXiv-print.css?v=20200611" /> <link rel="stylesheet" type="text/css" media="screen" href="/static/browse/0.3.4/css/browse_search.css" /> <script language="javascript" src="/static/browse/0.3.4/js/accordion.js" /></script> <link rel="canonical" href="https://arxiv.org/abs/2102.05918"/> <meta name="description" content="Abstract page for arXiv paper 2102.05918: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision"><meta property="og:type" content="website" /> <meta property="og:site_name" content="arXiv.org" /> <meta property="og:title" content="Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision" /> <meta property="og:url" content="https://arxiv.org/abs/2102.05918v2" /> <meta property="og:image" content="/static/browse/0.3.4/images/arxiv-logo-fb.png" /> <meta property="og:image:secure_url" content="/static/browse/0.3.4/images/arxiv-logo-fb.png" /> <meta property="og:image:width" content="1200" /> <meta property="og:image:height" content="700" /> <meta property="og:image:alt" content="arXiv logo"/> <meta property="og:description" content="Pre-trained representations are becoming crucial for many NLP and perception tasks. While representation learning in NLP has transitioned to training on raw text without human annotations, visual and vision-language representations still rely heavily on curated training datasets that are expensive or require expert knowledge. For vision applications, representations are mostly learned using datasets with explicit class labels such as ImageNet or OpenImages. For vision-language, popular datasets like Conceptual Captions, MSCOCO, or CLIP all involve a non-trivial data collection (and cleaning) process. This costly curation process limits the size of datasets and hence hinders the scaling of trained models. In this paper, we leverage a noisy dataset of over one billion image alt-text pairs, obtained without expensive filtering or post-processing steps in the Conceptual Captions dataset. A simple dual-encoder architecture learns to align visual and language representations of the image and text pairs using a contrastive loss. We show that the scale of our corpus can make up for its noise and leads to state-of-the-art representations even with such a simple learning scheme. Our visual representation achieves strong performance when transferred to classification tasks such as ImageNet and VTAB. The aligned visual and language representations enables zero-shot image classification and also set new state-of-the-art results on Flickr30K and MSCOCO image-text retrieval benchmarks, even when compared with more sophisticated cross-attention models. The representations also enable cross-modality search with complex text and text + image queries."/> <meta name="twitter:site" content="@arxiv"/> <meta name="twitter:card" content="summary"/> <meta name="twitter:title" content="Scaling Up Visual and Vision-Language Representation Learning With..."/> <meta name="twitter:description" content="Pre-trained representations are becoming crucial for many NLP and perception tasks. While representation learning in NLP has transitioned to training on raw text without human annotations, visual..."/> <meta name="twitter:image" content="https://static.arxiv.org/icons/twitter/arxiv-logo-twitter-square.png"/> <meta name="twitter:image:alt" content="arXiv logo"/> <link rel="stylesheet" media="screen" type="text/css" href="/static/browse/0.3.4/css/tooltip.css"/><link rel="stylesheet" media="screen" type="text/css" href="https://static.arxiv.org/js/bibex-dev/bibex.css?20200709"/> <script src="/static/browse/0.3.4/js/mathjaxToggle.min.js" type="text/javascript"></script> <script src="//code.jquery.com/jquery-latest.min.js" type="text/javascript"></script> <script src="//cdn.jsdelivr.net/npm/js-cookie@2/src/js.cookie.min.js" type="text/javascript"></script> <script src="//cdn.jsdelivr.net/npm/dompurify@2.3.5/dist/purify.min.js"></script> <script src="/static/browse/0.3.4/js/toggle-labs.js?20241022" type="text/javascript"></script> <script src="/static/browse/0.3.4/js/cite.js" type="text/javascript"></script><meta name="citation_title" content="Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision" /><meta name="citation_author" content="Jia, Chao" /><meta name="citation_author" content="Yang, Yinfei" /><meta name="citation_author" content="Xia, Ye" /><meta name="citation_author" content="Chen, Yi-Ting" /><meta name="citation_author" content="Parekh, Zarana" /><meta name="citation_author" content="Pham, Hieu" /><meta name="citation_author" content="Le, Quoc V." /><meta name="citation_author" content="Sung, Yunhsuan" /><meta name="citation_author" content="Li, Zhen" /><meta name="citation_author" content="Duerig, Tom" /><meta name="citation_date" content="2021/02/11" /><meta name="citation_online_date" content="2021/06/11" /><meta name="citation_pdf_url" content="http://arxiv.org/pdf/2102.05918" /><meta name="citation_arxiv_id" content="2102.05918" /><meta name="citation_abstract" content="Pre-trained representations are becoming crucial for many NLP and perception tasks. While representation learning in NLP has transitioned to training on raw text without human annotations, visual and vision-language representations still rely heavily on curated training datasets that are expensive or require expert knowledge. For vision applications, representations are mostly learned using datasets with explicit class labels such as ImageNet or OpenImages. For vision-language, popular datasets like Conceptual Captions, MSCOCO, or CLIP all involve a non-trivial data collection (and cleaning) process. This costly curation process limits the size of datasets and hence hinders the scaling of trained models. In this paper, we leverage a noisy dataset of over one billion image alt-text pairs, obtained without expensive filtering or post-processing steps in the Conceptual Captions dataset. A simple dual-encoder architecture learns to align visual and language representations of the image and text pairs using a contrastive loss. We show that the scale of our corpus can make up for its noise and leads to state-of-the-art representations even with such a simple learning scheme. Our visual representation achieves strong performance when transferred to classification tasks such as ImageNet and VTAB. The aligned visual and language representations enables zero-shot image classification and also set new state-of-the-art results on Flickr30K and MSCOCO image-text retrieval benchmarks, even when compared with more sophisticated cross-attention models. The representations also enable cross-modality search with complex text and text + image queries." /> </head> <body class="with-cu-identity"> <div class="flex-wrap-footer"> <header> <a href="#content" class="is-sr-only">Skip to main content</a>  <div class="columns is-vcentered is-hidden-mobile" id="cu-identity"> <div class="column" id="cu-logo"> <a href="https://www.cornell.edu/"><img src="/static/browse/0.3.4/images/icons/cu/cornell-reduced-white-SMALL.svg" alt="Cornell University" /></a> </div><div class="column" id="support-ack"> <span id="support-ack-url">We gratefully acknowledge support from the Simons Foundation, <a href="https://info.arxiv.org/about/ourmembers.html">member institutions</a>, and all contributors.</span> <a href="https://info.arxiv.org/about/donate.html" class="btn-header-donate">Donate</a> </div> </div> <div id="header" class="is-hidden-mobile"> <a aria-hidden="true" tabindex="-1" href="/IgnoreMe"></a> <div class="header-breadcrumbs is-hidden-mobile"> <a href="/"><img src="/static/browse/0.3.4/images/arxiv-logo-one-color-white.svg" alt="arxiv logo" style="height:40px;"/></a> <span>></span> <a href="/list/cs/recent">cs</a> <span>></span> arXiv:2102.05918 </div> <div class="search-block level-right"> <form class="level-item mini-search" method="GET" action="https://arxiv.org/search"> <div class="field has-addons"> <div class="control"> <input class="input is-small" type="text" name="query" placeholder="Search..." aria-label="Search term or terms" /> <p class="help"><a href="https://info.arxiv.org/help">Help</a> | <a href="https://arxiv.org/search/advanced">Advanced Search</a></p> </div> <div class="control"> <div class="select is-small"> <select name="searchtype" aria-label="Field to search"> <option value="all" selected="selected">All fields</option> <option value="title">Title</option> <option value="author">Author</option> <option value="abstract">Abstract</option> <option value="comments">Comments</option> <option value="journal_ref">Journal reference</option> <option value="acm_class">ACM classification</option> <option value="msc_class">MSC classification</option> <option value="report_num">Report number</option> <option value="paper_id">arXiv identifier</option> <option value="doi">DOI</option> <option value="orcid">ORCID</option> <option value="author_id">arXiv author ID</option> <option value="help">Help pages</option> <option value="full_text">Full text</option> </select> </div> </div> <input type="hidden" name="source" value="header"> <button class="button is-small is-cul-darker">Search</button> </div> </form> </div> </div> <div class="mobile-header"> <div class="columns is-mobile"> <div class="column logo-arxiv"><a href="https://arxiv.org/"><img src="/static/browse/0.3.4/images/arxiv-logomark-small-white.svg" alt="arXiv logo" style="height:60px;" /></a></div> <div class="column logo-cornell"><a href="https://www.cornell.edu/"> <picture> <source media="(min-width: 501px)" srcset="/static/browse/0.3.4/images/icons/cu/cornell-reduced-white-SMALL.svg 400w" sizes="400w" /> <source srcset="/static/browse/0.3.4/images/icons/cu/cornell_seal_simple_black.svg 2x" /> <img src="/static/browse/0.3.4/images/icons/cu/cornell-reduced-white-SMALL.svg" alt="Cornell University Logo" /> </picture> </a></div> <div class="column nav" id="toggle-container" role="menubar"> <button class="toggle-control"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-white"><title>open search</title><path d="M505 442.7L405.3 343c-4.5-4.5-10.6-7-17-7H372c27.6-35.3 44-79.7 44-128C416 93.1 322.9 0 208 0S0 93.1 0 208s93.1 208 208 208c48.3 0 92.7-16.4 128-44v16.3c0 6.4 2.5 12.5 7 17l99.7 99.7c9.4 9.4 24.6 9.4 33.9 0l28.3-28.3c9.4-9.4 9.4-24.6.1-34zM208 336c-70.7 0-128-57.2-128-128 0-70.7 57.2-128 128-128 70.7 0 128 57.2 128 128 0 70.7-57.2 128-128 128z"/></svg></button> <div class="mobile-toggle-block toggle-target"> <form class="mobile-search-form" method="GET" action="https://arxiv.org/search"> <div class="field has-addons"> <input class="input" type="text" name="query" placeholder="Search..." aria-label="Search term or terms" /> <input type="hidden" name="source" value="header"> <input type="hidden" name="searchtype" value="all"> <button class="button">GO</button> </div> </form> </div> <button class="toggle-control"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512" class="icon filter-white" role="menu"><title>open navigation menu</title><path d="M16 132h416c8.837 0 16-7.163 16-16V76c0-8.837-7.163-16-16-16H16C7.163 60 0 67.163 0 76v40c0 8.837 7.163 16 16 16zm0 160h416c8.837 0 16-7.163 16-16v-40c0-8.837-7.163-16-16-16H16c-8.837 0-16 7.163-16 16v40c0 8.837 7.163 16 16 16zm0 160h416c8.837 0 16-7.163 16-16v-40c0-8.837-7.163-16-16-16H16c-8.837 0-16 7.163-16 16v40c0 8.837 7.163 16 16 16z"/ ></svg></button> <div class="mobile-toggle-block toggle-target"> <nav class="mobile-menu" aria-labelledby="mobilemenulabel"> <h2 id="mobilemenulabel">quick links</h2> <ul> <li><a href="https://arxiv.org/login">Login</a></li> <li><a href="https://info.arxiv.org/help">Help Pages</a></li> <li><a href="https://info.arxiv.org/about">About</a></li> </ul> </nav> </div> </div> </div> </div> </header> <main> <div id="content"> <div id="abs-outer"> <div class="leftcolumn"> <div class="subheader"> <h1>Computer Science > Computer Vision and Pattern Recognition</h1> </div> <div class="header-breadcrumbs-mobile"> <strong>arXiv:2102.05918</strong> (cs) </div> <link rel="stylesheet" type="text/css" href="/static/base/1.0.1/css/abs.css"> <div id="content-inner"> <div id="abs"> <div class="dateline"> [Submitted on 11 Feb 2021 (<a href="https://arxiv.org/abs/2102.05918v1">v1</a>), last revised 11 Jun 2021 (this version, v2)]</div> <h1 class="title mathjax"><span class="descriptor">Title:</span>Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision</h1> <div class="authors"><span class="descriptor">Authors:</span><a href="https://arxiv.org/search/cs?searchtype=author&query=Jia,+C" rel="nofollow">Chao Jia</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+Y" rel="nofollow">Yinfei Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xia,+Y" rel="nofollow">Ye Xia</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Y" rel="nofollow">Yi-Ting Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Parekh,+Z" rel="nofollow">Zarana Parekh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pham,+H" rel="nofollow">Hieu Pham</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Le,+Q+V" rel="nofollow">Quoc V. Le</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sung,+Y" rel="nofollow">Yunhsuan Sung</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+Z" rel="nofollow">Zhen Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Duerig,+T" rel="nofollow">Tom Duerig</a></div> <div id="download-button-info" hidden>View a PDF of the paper titled Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision, by Chao Jia and 9 other authors</div> <a class="mobile-submission-download" href="/pdf/2102.05918">View PDF</a> <blockquote class="abstract mathjax"> <span class="descriptor">Abstract:</span>Pre-trained representations are becoming crucial for many NLP and perception tasks. While representation learning in NLP has transitioned to training on raw text without human annotations, visual and vision-language representations still rely heavily on curated training datasets that are expensive or require expert knowledge. For vision applications, representations are mostly learned using datasets with explicit class labels such as ImageNet or OpenImages. For vision-language, popular datasets like Conceptual Captions, MSCOCO, or CLIP all involve a non-trivial data collection (and cleaning) process. This costly curation process limits the size of datasets and hence hinders the scaling of trained models. In this paper, we leverage a noisy dataset of over one billion image alt-text pairs, obtained without expensive filtering or post-processing steps in the Conceptual Captions dataset. A simple dual-encoder architecture learns to align visual and language representations of the image and text pairs using a contrastive loss. We show that the scale of our corpus can make up for its noise and leads to state-of-the-art representations even with such a simple learning scheme. Our visual representation achieves strong performance when transferred to classification tasks such as ImageNet and VTAB. The aligned visual and language representations enables zero-shot image classification and also set new state-of-the-art results on Flickr30K and MSCOCO image-text retrieval benchmarks, even when compared with more sophisticated cross-attention models. The representations also enable cross-modality search with complex text and text + image queries. </blockquote>  <div class="metatable"> <table summary="Additional metadata"> <tr> <td class="tablecell label">Comments:</td> <td class="tablecell comments mathjax">ICML 2021</td> </tr> <tr> <td class="tablecell label">Subjects:</td> <td class="tablecell subjects"> <span class="primary-subject">Computer Vision and Pattern Recognition (cs.CV)</span>; Computation and Language (cs.CL); Machine Learning (cs.LG)</td> </tr><tr> <td class="tablecell label">Cite as:</td> <td class="tablecell arxivid"><span class="arxivid"><a href="https://arxiv.org/abs/2102.05918">arXiv:2102.05918</a> [cs.CV]</span></td> </tr> <tr> <td class="tablecell label"> </td> <td class="tablecell arxividv">(or <span class="arxivid"> <a href="https://arxiv.org/abs/2102.05918v2">arXiv:2102.05918v2</a> [cs.CV]</span> for this version) </td> </tr> <tr> <td class="tablecell label"> </td> <td class="tablecell arxivdoi"> <a href="https://doi.org/10.48550/arXiv.2102.05918" id="arxiv-doi-link">https://doi.org/10.48550/arXiv.2102.05918</a><div class="button-and-tooltip"> <button class="more-info" aria-describedby="more-info-desc-1"> <svg height="15" role="presentation" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M256 8C119.043 8 8 119.083 8 256c0 136.997 111.043 248 248 248s248-111.003 248-248C504 119.083 392.957 8 256 8zm0 110c23.196 0 42 18.804 42 42s-18.804 42-42 42-42-18.804-42-42 18.804-42 42-42zm56 254c0 6.627-5.373 12-12 12h-88c-6.627 0-12-5.373-12-12v-24c0-6.627 5.373-12 12-12h12v-64h-12c-6.627 0-12-5.373-12-12v-24c0-6.627 5.373-12 12-12h64c6.627 0 12 5.373 12 12v100h12c6.627 0 12 5.373 12 12v24z" class=""></path></svg> <span class="visually-hidden">Focus to learn more</span> </button>  <div role="tooltip" id="more-info-desc-1"> <span class="left-corner"></span> arXiv-issued DOI via DataCite</div> </div> </td> </tr> <tr> <td class="tablecell label">Journal reference:</td> <td class="tablecell jref">International Conference on Machine Learning 2021</td> </tr> </table> </div> </div> </div> <div class="submission-history"> <h2>Submission history</h2> From: Chao Jia [<a href="/show-email/7a5c30d2/2102.05918" rel="nofollow">view email</a>] <br/> <strong><a href="/abs/2102.05918v1" rel="nofollow">[v1]</a></strong> Thu, 11 Feb 2021 10:08:12 UTC (1,627 KB)<br/> <strong>[v2]</strong> Fri, 11 Jun 2021 07:51:39 UTC (1,658 KB)<br/> </div> </div>  <div class="extra-services"> <div class="full-text"> <a name="other"></a> <span class="descriptor">Full-text links:</span> <h2>Access Paper:</h2> <ul> <div id="download-button-info" hidden> View a PDF of the paper titled Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision, by Chao Jia and 9 other authors</div><li><a href="/pdf/2102.05918" aria-describedby="download-button-info" accesskey="f" class="abs-button download-pdf">View PDF</a></li><li><a href="/src/2102.05918" class="abs-button download-eprint">TeX Source</a></li><li><a href="/format/2102.05918" class="abs-button download-format">Other Formats</a></li></ul> <div class="abs-license"><a href="http://arxiv.org/licenses/nonexclusive-distrib/1.0/" title="Rights to this article">view license</a></div> </div>  <div class="browse"> Current browse context: <div class="current">cs.CV</div> <div class="prevnext"> <span class="arrow"> <a class="abs-button prev-url" href="/prevnext?id=2102.05918&function=prev&context=cs.CV" accesskey="p" title="previous in cs.CV (accesskey p)" rel="nofollow">< prev</a> </span> <span class="is-hidden-mobile">  |  </span> <span class="arrow"> <a class="abs-button next-url" href="/prevnext?id=2102.05918&function=next&context=cs.CV" accesskey="n" title="next in cs.CV (accesskey n)" rel="nofollow">next ></a> </span><br/> </div><div class="list"> <a class="abs-button abs-button-grey abs-button-small context-new" href="/list/cs.CV/new" rel="nofollow">new</a> <span class="is-hidden-mobile"> | </span> <a class="abs-button abs-button-grey abs-button-small context-recent" href="/list/cs.CV/recent" rel="nofollow">recent</a> <span class="is-hidden-mobile"> | </span><a class="abs-button abs-button-grey abs-button-small context-id" href="/list/cs.CV/2021-02" rel="nofollow">2021-02</a> </div><div class="abs-switch-cat"> Change to browse by: <div class="switch context-change"> <a href="/abs/2102.05918?context=cs" rel="nofollow">cs</a><br class="is-hidden-mobile"> <a class="subclass" href="/abs/2102.05918?context=cs.CL" rel="nofollow">cs.CL</a><br class="is-hidden-mobile"> <a class="subclass" href="/abs/2102.05918?context=cs.LG" rel="nofollow">cs.LG</a><br class="is-hidden-mobile"> </div> </div> </div> <div class="extra-ref-cite"> <h3>References & Citations</h3> <ul> <li><a class="abs-button abs-button-small cite-ads" href="https://ui.adsabs.harvard.edu/abs/arXiv:2102.05918">NASA ADS</a></li><li><a class="abs-button abs-button-small cite-google-scholar" href="https://scholar.google.com/scholar_lookup?arxiv_id=2102.05918" target="_blank" rel="noopener">Google Scholar</a></li> <li><a class="abs-button abs-button-small cite-semantic-scholar" href="https://api.semanticscholar.org/arXiv:2102.05918" target="_blank" rel="noopener">Semantic Scholar</a></li> </ul> <div style="clear:both;"></div> </div> <div class="extra-general"> <div class="what-is-this"> <h3><a class="abs-button abs-button-grey abs-button-small trackback-link" href="/tb/2102.05918"> 2 blog links</a></h3> (<a href="https://info.arxiv.org/help/trackback.html" class="trackback-help">what is this?</a>) </div> </div> <div class="dblp"> <h3><a href="https://dblp.uni-trier.de">DBLP</a> - CS Bibliography</h3> <div class="list"> <a href="https://dblp.uni-trier.de/db/journals/corr/corr2102.html#abs-2102-05918" title="listing on DBLP">listing</a> | <a href="https://dblp.uni-trier.de/rec/bibtex/journals/corr/abs-2102-05918" title="DBLP bibtex record">bibtex</a> </div> <div class="list"> <a href="https://dblp.uni-trier.de/search/author?author=Chao%20Jia" title="DBLP author search">Chao Jia</a><br/><a href="https://dblp.uni-trier.de/search/author?author=Yinfei%20Yang" title="DBLP author search">Yinfei Yang</a><br/><a href="https://dblp.uni-trier.de/search/author?author=Ye%20Xia" title="DBLP author search">Ye Xia</a><br/><a href="https://dblp.uni-trier.de/search/author?author=Yi-Ting%20Chen" title="DBLP author search">Yi-Ting Chen</a><br/><a href="https://dblp.uni-trier.de/search/author?author=Zarana%20Parekh" title="DBLP author search">Zarana Parekh</a> <div class="list">…</div> </div> </div><div class='extra-ref-cite'> <a id='bib-cite-css' hidden='true' href='/static/browse/0.3.4/css/cite.css'>a</a> <span id='bib-cite-trigger' class="bib-cite-button abs-button">export BibTeX citation</span> <span id='bib-cite-loading' hidden='true'>Loading...</span> </div> <div id='bib-cite-modal' class='bib-modal' hidden='true'> <div class='bib-modal-content'> <div class='bib-modal-title'> <h2>BibTeX formatted citation</h2> <span class='bib-modal-close' >×</span> </div> <div> <textarea id='bib-cite-target' class="bib-citation-content" aria-label="loading the citation">loading...</textarea> </div> <div> <span>Data provided by: </span> <a id='bib-cite-source-api'></a> </div> </div> </div><div class="bookmarks"> <div><h3>Bookmark</h3></div><a class="abs-button abs-button-grey abs-button-small" href="http://www.bibsonomy.org/BibtexHandler?requTask=upload&url=https://arxiv.org/abs/2102.05918&description=Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision" title="Bookmark on BibSonomy"> <img src="/static/browse/0.3.4/images/icons/social/bibsonomy.png" alt="BibSonomy logo"/> </a> <a class="abs-button abs-button-grey abs-button-small" href="https://reddit.com/submit?url=https://arxiv.org/abs/2102.05918&title=Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision" title="Bookmark on Reddit"> <img src="/static/browse/0.3.4/images/icons/social/reddit.png" alt="Reddit logo"/> </a> </div> </div>   <div id="labstabs"> <div class="labstabs"><input type="radio" name="tabs" id="tabone"checked="checked"> <label for="tabone">Bibliographic Tools</label> <div class="tab labs-display-bib"> <h1>Bibliographic and Citation Tools</h1> <div class="toggle"> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="bibex-toggle" type="checkbox" class="lab-toggle"> <span class="slider"></span> <span class="is-sr-only">Bibliographic Explorer Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-bibex">Bibliographic Explorer</span> <em>(<a href="https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer">What is the Explorer?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="connectedpapers-toggle" type="checkbox" class="lab-toggle" data-script-url="/static/browse/0.3.4/js/connectedpapers.js" aria-labelledby="label-for-connected-papers"> <span class="slider"></span> <span class="is-sr-only">Connected Papers Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-connected-papers">Connected Papers</span> <em>(<a href="https://www.connectedpapers.com/about" target="_blank">What is Connected Papers?</a>)</em> </div> </div><div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="litmaps-toggle" type="checkbox" class="lab-toggle" data-script-url="/static/browse/0.3.4/js/litmaps.js?20210617" aria-labelledby="label-for-litmaps"> <span class="slider"></span> <span class="is-sr-only">Litmaps Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-litmaps">Litmaps</span> <em>(<a href="https://www.litmaps.co/" target="_blank">What is Litmaps?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="scite-toggle" type="checkbox" class="lab-toggle" data-script-url="/static/browse/0.3.4/js/scite.js?20210617" aria-labelledby="label-for-scite"> <span class="slider"></span> <span class="is-sr-only">scite.ai Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-scite">scite Smart Citations</span> <em>(<a href="https://www.scite.ai/" target="_blank">What are Smart Citations?</a>)</em> </div> </div> </div> <div class="labs-content-placeholder labs-display" style="display: none;"></div> <div style="min-height: 15px" id="connectedpapers-output"></div> <div style="min-height: 15px" id="litmaps-open-in"></div> <div style="min-height: 15px" id="scite-open-in"></div> </div> <input type="radio" name="tabs" id="tabtwo"> <label for="tabtwo">Code, Data, Media</label> <div class="tab"> <h1>Code, Data and Media Associated with this Article</h1> <div class="toggle"> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="alphaxiv-toggle" data-script-url="/static/browse/0.3.4/js/alphaxiv.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-alphaxiv"> <span class="slider"></span> <span class="is-sr-only">alphaXiv Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-alphaxiv">alphaXiv</span> <em>(<a href="https://alphaxiv.org/" target="_blank">What is alphaXiv?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="catalyzex-toggle" data-script-url="/static/browse/0.3.4/js/catalyzex.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-cx"> <span class="slider"></span> <span class="is-sr-only">Links to Code Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-cx">CatalyzeX Code Finder for Papers</span> <em>(<a href="https://www.catalyzex.com" target="_blank">What is CatalyzeX?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="dagshub-toggle" data-script-url="/static/browse/0.3.4/js/dagshub.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-dagshub"> <span class="slider"></span> <span class="is-sr-only">DagsHub Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-dagshub">DagsHub</span> <em>(<a href="https://dagshub.com/" target="_blank">What is DagsHub?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="gotitpub-toggle" data-script-url="/static/browse/0.3.4/js/gotitpub.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-gotitpub"> <span class="slider"></span> <span class="is-sr-only">GotitPub Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-gotitpub">Gotit.pub</span> <em>(<a href="http://gotit.pub/faq" target="_blank">What is GotitPub?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="huggingface-toggle" data-script-url="/static/browse/0.3.4/js/huggingface.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-huggingface"> <span class="slider"></span> <span class="is-sr-only">Huggingface Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-huggingface">Hugging Face</span> <em>(<a href="https://huggingface.co/huggingface" target="_blank">What is Huggingface?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="paperwithcode-toggle" data-script-url="/static/browse/0.3.4/js/paperswithcode.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-pwc"> <span class="slider"></span> <span class="is-sr-only">Links to Code Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-pwc">Papers with Code</span> <em>(<a href="https://paperswithcode.com/" target="_blank">What is Papers with Code?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="sciencecast-toggle" data-script-url="/static/browse/0.3.4/js/sciencecast.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-sciencecast"> <span class="slider"></span> <span class="is-sr-only">ScienceCast Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-sciencecast">ScienceCast</span> <em>(<a href="https://sciencecast.org/welcome" target="_blank">What is ScienceCast?</a>)</em> </div> </div> </div> <div id="alphaxiv-output" style="display:none"></div> <div id="catalyzex-output" style="display:none"></div> <div id="dagshub-output" style="display:none"></div> <div id="gotitpub-output" style="display:none"></div> <div id="pwc-output" style="display:none"></div> <div id="pwc-data-output" style="display:none"></div> <div id="sciencecast-output" style="display:none"></div> <div id="huggingface-output" style="display:none"></div> </div> <input type="radio" name="tabs" id="labstabs-demos-input"> <label for="labstabs-demos-input" id="labstabs-demos-label">Demos</label> <div class="tab"> <h1>Demos</h1> <div class="toggle"> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="replicate-toggle" data-script-url="/static/browse/0.3.4/js/replicate.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-replicate"> <span class="slider"></span> <span class="is-sr-only">Replicate Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-replicate">Replicate</span> <em>(<a href="https://replicate.com/docs/arxiv/about" target="_blank">What is Replicate?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="spaces-toggle" data-script-url="/static/browse/0.3.4/js/spaces.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-spaces"> <span class="slider"></span> <span class="is-sr-only">Spaces Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-spaces">Hugging Face Spaces</span> <em>(<a href="https://huggingface.co/docs/hub/spaces" target="_blank">What is Spaces?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="txyz-toggle" data-script-url="/static/browse/0.3.4/js/txyz.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-txyz"> <span class="slider"></span> <span class="is-sr-only">Spaces Toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-txyz">TXYZ.AI</span> <em>(<a href="https://txyz.ai" target="_blank">What is TXYZ.AI?</a>)</em> </div> </div> </div> <div id="replicate-output"></div> <div id="spaces-output"></div> <div id="txyz-output"></div> </div> <input type="radio" name="tabs" id="tabfour"> <label for="tabfour">Related Papers</label> <div class="tab"> <h1>Recommenders and Search Tools</h1> <div class="toggle"> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="influenceflower-toggle" data-script-url="/static/browse/0.3.4/js/influenceflower.js" type="checkbox" class="lab-toggle" aria-labelledby="label-for-influenceflower"> <span class="slider"></span> <span class="is-sr-only">Link to Influence Flower</span> </label> </div> <div class="column lab-name"> <span id="label-for-influenceflower">Influence Flower</span> <em>(<a href="https://influencemap.cmlab.dev/" target="_blank">What are Influence Flowers?</a>)</em> </div> </div> <div class="columns is-mobile lab-row"> <div class="column lab-switch"> <label class="switch"> <input id="core-recommender-toggle" type="checkbox" class="lab-toggle" aria-labelledby="label-for-core"> <span class="slider"></span> <span class="is-sr-only">Core recommender toggle</span> </label> </div> <div class="column lab-name"> <span id="label-for-core">CORE Recommender</span> <em>(<a href="https://core.ac.uk/services/recommender">What is CORE?</a>)</em> </div> </div></div> <div id="influenceflower-output"></div> <div id="influenceflower-output-graph" style="display:none"> <ul class="flower-tabs"> <li class="active"><a class="btn tab-btn" onclick="openTab(event, 'tab-author')">Author</a></li> <li><a class="btn tab-btn" onclick="openTab(event, 'tab-venue')">Venue</a></li> <li><a class="btn tab-btn" onclick="openTab(event, 'tab-inst')">Institution</a></li> <li><a class="btn tab-btn" onclick="openTab(event, 'tab-topic')">Topic</a></li> </ul> <div class="flower-tab-content"> <div class="tab-flower active" id="tab-author"><svg id="flower-graph-author"></svg></div> <div class="tab-flower" id="tab-venue"><svg id="flower-graph-venue"></svg></div> <div class="tab-flower" id="tab-inst"><svg id="flower-graph-inst"></svg></div> <div class="tab-flower" id="tab-topic"><svg id="flower-graph-topic"></svg></div> </div> </div> <div id="coreRecommenderOutput"></div> <div id="iarxivOutput"></div> </div> <input type="radio" name="tabs" id="tabfive"> <label for="tabfive"> About arXivLabs </label> <div class="tab"> <div class="columns"> <div class="column"> <h1>arXivLabs: experimental projects with community collaborators</h1> <p>arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.</p> <p>Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.</p> <p>Have an idea for a project that will add value for arXiv's community? <a href="https://info.arxiv.org/labs/index.html"><strong>Learn more about arXivLabs</strong></a>.</p> </div> <div class="column is-narrow is-full-mobile"> <p class="icon-labs"><svg xmlns="http://www.w3.org/2000/svg" role="presentation" viewBox="0 0 635.572 811"><path d="M175.6 676v27h-27v-27zm-54 27v27h27v-27zm-27 27v27h27v-27zm396-54v27h-27v-27zm0 27v27h27v-27zm27 27v27h27v-27zm-27-414h27v27h-27zm27 0h27v-27h-27zm27-27h27v-27h-27zm-396 45h-27v-27h27zm-27-54h-27v27h27zm-27-27h-27v27h27z"/><path d="M94.6 730v27h-27v-27zm477 0v27h-27v-27zm-27-495h27v27h-27zm-450 18h-27v-27h27zm477 9h27v27h-27zm-54 495h27v27h-27zm-423 0h27v27h-27zm-54-504h27v27h-27z" fill="#666"/><path d="M67.6 730v27h-27v-27zm54 54v27h-27v-27zm0-108v27h27v-27zm-27 27v27h27v-27zm-81 0v27h27v-27zm585 27v27h-27v-27zm-108-54v27h27v-27zm27 27v27h27v-27zm81 0v27h27v-27zm-54-495h27v27h-27zm-54 108h27v-27h-27zm27-27h27v-27h-27zm0-81h27v-27h-27zm-423 18h-27v-27h27zm54 54h-27v27h27zm-27-27h-27v27h27zm0-81h-27v27h27zm423 612v27h-27v-27zm81-522v27h-27v-27zm-585-9v27h-27v-27z" fill="#999"/><path d="M94.6 784v27h-27v-27zm-27-27v27h27v-27zm-27-54v27h27v-27zm27 0v27h27v-27zm0-27v27h27v-27zm27 0v27h27v-27zm0-27v27h27v-27zm27 0v27h27v-27zm-108 81v27h27v-27zm558 54v27h-27v-27zm-27-27v27h27v-27zm27-54v27h27v-27zm-27 0v27h27v-27zm0-27v27h27v-27zm-27 0v27h27v-27zm0-27v27h27v-27zm-27 0v27h27v-27zm108 81v27h27v-27zm0-495h27v27h-27zm-27 27h27v-27h-27zm-54-27h27v-27h-27zm0 27h27v-27h-27zm-27 0h27v-27h-27zm0 27h27v-27h-27zm-27 0h27v-27h-27zm0 27h27v-27h-27zm81-108h27v-27h-27zm-504 45h-27v-27h27zm27-27h-27v27h27zm54-27h-27v27h27zm0 27h-27v27h27zm27 0h-27v27h27zm0 27h-27v27h27zm27 0h-27v27h27zm0 27h-27v27h27zm-81-108h-27v27h27z" fill="#ccc"/><path d="M598.6 665.1H41.5C-76.5 667 176 280.2 176 280.2h53a46.5 46.5 0 0162.8-56.3 29.2 29.2 0 1128.5 35.9h-1a46.5 46.5 0 01-1.5 20.3l142.5-.1s255.3 387 138.3 385.1zM291 181a29.3 29.3 0 10-29.2-29.3A29.3 29.3 0 00291 181zm65.4-66.8a22.4 22.4 0 10-22.5-22.4 22.4 22.4 0 0022.5 22.4z" fill="#fc0"/><path d="M245.5 172V10h153v162s324 495 198 495h-558c-126 0 207-495 207-495zm126 54h56m-13 72h56m-9 72h56m-20 72h56m-22 72h56m-29 72h56m-457-45c20.8 41.7 87.3 81 160.7 81 72.1 0 142.1-38.2 163.4-81" fill="none" stroke="#000" stroke-miterlimit="10" stroke-width="20"/><path d="M273.3 421.7c0 31-9.8 56.3-21.9 56.3s-21.8-25.2-21.8-56.3 9.8-56.3 21.8-56.3 21.9 25.2 21.9 56.3zm114.4-56.3c-12 0-21.8 25.2-21.8 56.3s9.7 56.3 21.8 56.3 21.9-25.2 21.9-56.3-9.8-56.3-21.9-56.3zM150.1 526.6c-18.2 6.7-27.5 22.9-23.2 30.2s14.8-5.5 33-12.2 37.4-4.9 33-12.2-24.5-12.6-42.8-5.8zm296 5.8c-4.2 7.3 14.9 5.5 33.1 12.2s28.7 19.5 33 12.2-5-23.5-23.2-30.2-38.5-1.5-42.8 5.8z"/></svg></p> </div> </div> </div> </div> </div>  <div class="endorsers"> <a href="/auth/show-endorsers/2102.05918" class="endorser-who" rel="nofollow">Which authors of this paper are endorsers?</a> | <a id="mathjax_toggle" href="javascript:setMathjaxCookie()">Disable MathJax</a> (<a href="https://info.arxiv.org/help/mathjax.html">What is MathJax?</a>) <span class="help" style="font-style: normal; float: right; margin-top: 0; margin-right: 1em;"></span> </div> <script type="text/javascript" language="javascript">mathjaxToggle();</script> </div> </div> </main> <footer style="clear: both;"> <div class="columns is-desktop" role="navigation" aria-label="Secondary" style="margin: -0.75em -0.75em 0.75em -0.75em">  <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>contact arXiv</title><desc>Click here to contact arXiv</desc><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg> <a href="https://info.arxiv.org/help/contact.html"> Contact</a> </li> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>subscribe to arXiv mailings</title><desc>Click here to subscribe</desc><path d="M476 3.2L12.5 270.6c-18.1 10.4-15.8 35.6 2.2 43.2L121 358.4l287.3-253.2c5.5-4.9 13.3 2.6 8.6 8.3L176 407v80.5c0 23.6 28.5 32.9 42.5 15.8L282 426l124.6 52.2c14.2 6 30.4-2.9 33-18.2l72-432C515 7.8 493.3-6.8 476 3.2z"/></svg> <a href="https://info.arxiv.org/help/subscribe"> Subscribe</a> </li> </ul> </div> </div> </div>   <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/help/license/index.html">Copyright</a></li> <li><a href="https://info.arxiv.org/help/policies/privacy_policy.html">Privacy Policy</a></li> </ul> </div> <div class="column sorry-app-links"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/help/web_accessibility.html">Web Accessibility Assistance</a></li> <li> <p class="help"> <a class="a11y-main-link" href="https://status.arxiv.org" target="_blank">arXiv Operational Status <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 256 512" class="icon filter-dark_grey" role="presentation"><path d="M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z"/></svg></a><br> Get status notifications via <a class="is-link" href="https://subscribe.sorryapp.com/24846f03/email/new" target="_blank"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg>email</a> or <a class="is-link" href="https://subscribe.sorryapp.com/24846f03/slack/new" target="_blank"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512" class="icon filter-black" role="presentation"><path d="M94.12 315.1c0 25.9-21.16 47.06-47.06 47.06S0 341 0 315.1c0-25.9 21.16-47.06 47.06-47.06h47.06v47.06zm23.72 0c0-25.9 21.16-47.06 47.06-47.06s47.06 21.16 47.06 47.06v117.84c0 25.9-21.16 47.06-47.06 47.06s-47.06-21.16-47.06-47.06V315.1zm47.06-188.98c-25.9 0-47.06-21.16-47.06-47.06S139 32 164.9 32s47.06 21.16 47.06 47.06v47.06H164.9zm0 23.72c25.9 0 47.06 21.16 47.06 47.06s-21.16 47.06-47.06 47.06H47.06C21.16 243.96 0 222.8 0 196.9s21.16-47.06 47.06-47.06H164.9zm188.98 47.06c0-25.9 21.16-47.06 47.06-47.06 25.9 0 47.06 21.16 47.06 47.06s-21.16 47.06-47.06 47.06h-47.06V196.9zm-23.72 0c0 25.9-21.16 47.06-47.06 47.06-25.9 0-47.06-21.16-47.06-47.06V79.06c0-25.9 21.16-47.06 47.06-47.06 25.9 0 47.06 21.16 47.06 47.06V196.9zM283.1 385.88c25.9 0 47.06 21.16 47.06 47.06 0 25.9-21.16 47.06-47.06 47.06-25.9 0-47.06-21.16-47.06-47.06v-47.06h47.06zm0-23.72c-25.9 0-47.06-21.16-47.06-47.06 0-25.9 21.16-47.06 47.06-47.06h117.84c25.9 0 47.06 21.16 47.06 47.06 0 25.9-21.16 47.06-47.06 47.06H283.1z"/></svg>slack</a> </p> </li> </ul> </div> </div> </div>   </div> </footer> </div> <script src="/static/base/1.0.1/js/member_acknowledgement.js"></script> </body> </html>

CINXE.COM

[2102.05918] Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision