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Search & information retrieval

Improving how people discover, understand, and use information through advances in search and retrieval.

Current selections

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Publication

A Benchmark for Deep Information Synthesis

Debjit Paul, D. Murphy, Milan Gritta, Ronald Cardenas, V. Prokhorov, L. Bolliger, Aysim Toker, Roy Miles, Andreea-Maria Oncescu, Jasivan Sivakumar, Philipp Borchert, Ismail Elezi, Meiru Zhang, Kukjin Lee, Guchun Zhang, Jun Wang, Gerasimos Lampouras

ICLR 2026 | February 2026

Publication

A Tale of Two Graphs: Separating Knowledge Exploration from Outline Structure for Open-Ended Deep Research

Zhuofan Shi, M. Ma, Zekun Yao, Fangkai Yang, Jue Zhang, Dongge Han, Victor Ruhle, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang

ICML 2026 | February 2026

Publication

Welfarist Formulations for Diverse Similarity Search

Siddharth Barman, Nirjhar Das, Shivam Gupta, Kiran Shiragur

ICLR 2026 | February 2026

Project

Video

Microsoft Research India 2025 Highlights

January 19, 2026

Here are some highlights of the research and impact at Microsoft Research India in 2025, along with some glimpses of the lab milieu.

Microsoft Research India 2025 Key Highlights

05:52

Publication

Fine-tuning Small Language Models as Efficient Enterprise Search Relevance Labelers

Yue Kang, Zhuoyi Huang, Benji Schussheim, Diana Licon, Dina Atia, Shixing Cao, Jacob Danovitch, Kunho Kim, Billy Norcilien, Jonah Karpman, Mahmound Sayed, Mike Taylor, Tao Sun, Pavel Metrikov, Vipul Agarwal, Chris Quirk, Ye-Yi Wang, Nick Craswell, Irene Shaffer, Tianwei Chen, Sulaiman Vesal, Soundar Srinivasan

ArXiv | January 2026

Publication

Scalable Distributed Vector Search via Accuracy Preserving Index Construction

Yuming Xu, Qianxi Zhang, Qi Chen, Baotong Lu, Menghao Li, Philip Adams, Mingqin Li, Zengzhong Li, Jing Liu, Cheng Li, Fan Yang

December 2025

arXiv | December 2025

Group

Machine Intelligence

Advanced machine learning research, grounded in trust, efficiency, capability. The Machine Intelligence team at MSR Cambridge (UK) is dedicated to foundational machine-learning research, guided by the principles of responsible AI, collaboration, and scientific excellence. Our…

Publication

Incorporating Token Importance in Multi-Vector Retrieval

S. Archish, Ankit Garg, Kirankumar Shiragur, Neeraj Kayal

November 2025

arXiv | November 2025

Group

ODSP Applied Science

Shaping the future of content and collaboration in OneDrive and SharePoint The ODSP Applied Science team is shaping the future of content and collaboration by transforming OneDrive and SharePoint into a planet-scale, AI-native knowledge substrate,…

Publication

Chain-of-Retrieval Augmented Generation

Liang Wang, Haonan Chen, Nan Yang, Xiaolong Huang, Zhicheng Dou, Furu Wei

NeurIPS 2025 | October 2025

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