{"version":"1.0","provider_name":"Microsoft Research","provider_url":"https:\/\/www.microsoft.com\/en-us\/research","author_name":"Alexis Hagen","author_url":"https:\/\/www.microsoft.com\/en-us\/research\/people\/v-alhage\/","title":"VinVL: Advancing the state of the art for vision-language models - Microsoft Research","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"N6Pusb1XcK\"><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/blog\/vinvl-advancing-the-state-of-the-art-for-vision-language-models\/\">VinVL: Advancing the state of the art for vision-language models<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/blog\/vinvl-advancing-the-state-of-the-art-for-vision-language-models\/embed\/#?secret=N6Pusb1XcK\" width=\"600\" height=\"338\" title=\"&#8220;VinVL: Advancing the state of the art for vision-language models&#8221; &#8212; Microsoft Research\" data-secret=\"N6Pusb1XcK\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2021\/01\/1400x788_VinVL_still_no_logo-scaled.jpg","thumbnail_width":2560,"thumbnail_height":1442,"description":"Humans understand the world by perceiving and fusing information from multiple channels, such as images viewed by the eyes, voices heard by the ears, and other forms of sensory input. One of the core aspirations in AI is to develop algorithms that endow computers with a similar ability: to effectively learn from multimodal data like [&hellip;]"}