{"id":592723,"date":"2019-07-09T08:41:21","date_gmt":"2019-07-09T15:41:21","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/?post_type=msr-project&#038;p=592723"},"modified":"2026-10-22T13:43:11","modified_gmt":"2026-10-22T20:43:11","slug":"machine-reading-comprehension","status":"publish","type":"msr-project","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/project\/machine-reading-comprehension\/","title":{"rendered":"Machine Reading Comprehension"},"content":{"rendered":"<section class=\"mb-3 moray-highlight\">\n\t<div class=\"card-img-overlay mx-lg-0\">\n\t\t<div class=\"card-background  has-background- card-background--full-bleed\">\n\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"3840\" height=\"1440\" src=\"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-content\/uploads\/2019\/07\/MSR_QandAWebGraphics_HEADER_1920x720.jpg\" class=\"attachment-full size-full\" alt=\"Machine Reading Comprehension project\" style=\"\" srcset=\"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-content\/uploads\/2019\/07\/MSR_QandAWebGraphics_HEADER_1920x720.jpg 3840w, https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-content\/uploads\/2019\/07\/MSR_QandAWebGraphics_HEADER_1920x720-300x113.jpg 300w, https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-content\/uploads\/2019\/07\/MSR_QandAWebGraphics_HEADER_1920x720-768x288.jpg 768w, https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-content\/uploads\/2019\/07\/MSR_QandAWebGraphics_HEADER_1920x720-1024x384.jpg 1024w, https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-content\/uploads\/2019\/07\/MSR_QandAWebGraphics_HEADER_1920x720-1920x720.jpg 1920w, https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-content\/uploads\/2019\/07\/MSR_QandAWebGraphics_HEADER_1920x720-1600x600.jpg 1600w\" sizes=\"auto, (max-width: 3840px) 100vw, 3840px\" \/>\t\t<\/div>\n\t\t<!-- Foreground -->\n\t\t<div class=\"card-foreground d-flex mt-md-n5 my-lg-5 px-g px-lg-0\">\n\t\t\t<!-- Container -->\n\t\t\t<div class=\"container d-flex mt-md-n5 my-lg-5 \">\n\t\t\t\t<!-- Card wrapper -->\n\t\t\t\t<div class=\"w-100 w-lg-col-5\">\n\t\t\t\t\t<!-- Card -->\n\t\t\t\t\t<div class=\"card material-md-card py-5 px-md-5\">\n\t\t\t\t\t\t<div class=\"card-body \">\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n<h1 id=\"machine-reading-comprehension\" class=\"wp-block-heading h2\">Machine Reading Comprehension<\/h1>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n<p class=\"wp-block-paragraph\">Machine Reading Comprehension (MRC), or the ability to read and understand unstructured text and then answer questions about it remains a challenging task for computers. MRC is a growing field of research due to its potential in various enterprise applications, as well as the availability of MRC benchmarking datasets (MSMARCO, SQuAD, NewsQA, etc.)<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">At Microsoft Research Montreal, we are developing algorithms that can learn to answer questions about new documents with limited amount of training data, incorporate common sense, and leverage external knowledge about the world. Our primary goal is questioning-answering in the real world: we envision an experience where getting the answers you need to complex questions about your documents is simple, effective, and intuitive.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We&#8217;ve created an interactive demo that showcases the question answering technology developed using MRC.<\/p>\n\n\n","protected":false},"excerpt":{"rendered":"<p>Machine Reading Comprehension (MRC) is a growing field of research, due to its potential in various enterprise applications, as well as the availability of MRC benchmarking datasets.<\/p>\n","protected":false},"featured_media":596791,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-592723","msr-project","type-msr-project","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us","msr-archive-status-complete"],"msr_project_start":"2019-07-09","related-publications":[549276,558447,595504,546099,547374,558489,495110,549297,480471,466575,455568,445488,445494,455544,442251,445104,445113,445512,598555],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[599313,602724],"related-articles":[],"tab-content":[],"related-researchers":[{"type":"user_nicename","display_name":"Mahmoud Adada","user_id":37176,"people_section":"Section name 1","alias":"maadada"},{"type":"user_nicename","display_name":"Luiz Belussi","user_id":37080,"people_section":"Section name 1","alias":"lubeluss"},{"type":"user_nicename","display_name":"Tatsuro Oya","user_id":37140,"people_section":"Section name 1","alias":"taoy"},{"type":"user_nicename","display_name":"Dennis Zhuang","user_id":37401,"people_section":"Section name 1","alias":"enzhuang"}],"msr_research_lab":[437514,1148609],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/592723","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":10,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/592723\/revisions"}],"predecessor-version":[{"id":1190833,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/592723\/revisions\/1190833"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/media\/596791"}],"wp:attachment":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/media?parent=592723"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=592723"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=592723"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=592723"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=592723"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}