{"id":1160955,"date":"2026-02-09T15:53:27","date_gmt":"2026-02-09T23:53:27","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2026-03-11T04:32:57","modified_gmt":"2026-03-11T11:32:57","slug":"collab-ai-research","status":"publish","type":"msr-group","link":"https:\/\/www.microsoft.com\/en-us\/research\/group\/collab-ai-research\/","title":{"rendered":"Collab AI Research"},"content":{"rendered":"
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Collab AI Research<\/h1>\n\n\n\n

How Microsoft is using science and research to invent the future of collaboration<\/p>\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\n\n\n\n\n\n\n\n

Welcome to Collab AI<\/h2>\n\n\n\n

Collaboration is a central feature of how work gets done, involving coordination across people, tasks, and information sources. As AI systems increasingly contribute to shared workflows\u2014synthesizing discussions, generating alternatives, maintaining context, and supporting group decision processes that unfold across both synchronous and asynchronous interaction\u2014understanding how humans and AI function together in group settings has become a scientific and operational priority. This shift raises new questions about evolving intent, shared grounding, and how collective reasoning unfolds across time and modalities.<\/p>\n\n\n\n

Collab AI serves as Microsoft\u2019s research center dedicated to studying collaborative processes and building intelligent systems capable of participating in them. The work spans empirical studies of team interaction, computational models of shared context, dialogic representations that capture how knowledge is co\u2011created, and methods for enabling AI to engage in multi\u2011party alignment and decision\u2011making. Featured papers, talks, and research outputs explore emerging data, architectures, and evaluation frameworks for systems that operate not as single\u2011user tools, but as contributors to group activity.<\/p>\n\n\n\n

Dive in to explore the science behind collaborative AI\u2014and to engage with research aimed at creating intelligent systems that do more than assist individuals. The goal is AI that helps teams form collective purpose, sustain coherent dialogue, and work together more effectively than ever before across conversations, shared and co-authored artifacts, meetings, and organizational workflows.<\/p>\n\n\n\n

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Actions Speak Louder Than Prompts: Rethinking How LLMs Reason Over Graph Data<\/h3>\n\n\n\n

We conducted one of the largest controlled evaluations of LLMs for graph inference to date, spanning 14 datasets across four domains, multiple structural regimes, and a range of model sizes and capabilities. The result is a set of practical, actionable insights for people building systems that combine language models with structured data \u2013 whether in collaborative platforms, social networks, e-commerce, or beyond.<\/p>\n\n\n\n

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Read the blog<\/a><\/div>\n\n\n\n
Browse Collab AI News<\/a><\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n
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Science Corner<\/h2>\n\n\n\n

Here you will find talks, tutorials, and perspectives that examine how collaborative intelligence emerges and how AI systems can be designed to support joint work. The content is curated to surface new questions, challenge assumptions, and deepen your understanding of how humans and intelligent systems will work together next.<\/p>\n\n\n\n

Talks & thought pieces<\/h3>\n\n\n\n\n\n

Researcher spotlights<\/h3>\n\n\n\n\n\n

Paper spotlights<\/h3>\n\n\n\n\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

How Microsoft is using science and research to invent the future of collaboration Collaboration is a central feature of how work gets done, involving coordination across people, tasks, and information sources. As AI systems increasingly contribute to shared workflows\u2014synthesizing discussions, generating alternatives, maintaining context, and supporting group decision processes that unfold across both synchronous and […]<\/p>\n","protected":false},"featured_media":1161556,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_group_start":"","footnotes":""},"research-area":[13556,13554,13559],"msr-group-type":[243694],"msr-locale":[268875],"msr-impact-theme":[],"class_list":["post-1160955","msr-group","type-msr-group","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-research-area-human-computer-interaction","msr-research-area-social-sciences","msr-group-type-group","msr-locale-en_us"],"msr_group_start":"","msr_detailed_description":"","msr_further_details":"","msr_hero_images":[],"msr_research_lab":[],"related-researchers":[{"type":"user_nicename","display_name":"Jaime Teevan","user_id":33975,"people_section":"Leadership team","alias":"teevan"},{"type":"user_nicename","display_name":"Brent Hecht","user_id":38997,"people_section":"Leadership team","alias":"brhecht"},{"type":"user_nicename","display_name":"Antonio Criminisi","user_id":41790,"people_section":"Leadership team","alias":"acriminisi"},{"type":"user_nicename","display_name":"Evgeniy Gabrilovich","user_id":44083,"people_section":"Leadership team","alias":"egabrilovich"},{"type":"user_nicename","display_name":"Ryen W. 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