Research Theme: 1
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Keynotes, invited talks, and lectures
Information Access of the Oppressed: Envisioning Emancipatory Information Access Platforms
Starling Centre for Just Technologies and Just Societies
Virtual, March 2026 (upcoming)
Information Access of the Oppressed: Envisioning Emancipatory Information Access Platforms
Department of Information Studies, University College London
Virtual, March 2026 (upcoming)
Information Retrieval & Society
Information Retrieval Lab (IRLab), University of Amsterdam (UvA)
Virtual, March 2026 (upcoming)
Emancipatory Information Retrieval: Radically Reorienting Information Retrieval Research to Resist Corporate and Authoritarian Capture of our Information Ecosystems
Forum for Information Retrieval Evaluation (FIRE)
Virtual, December 2025
SlideShare | PPT | Recording
Sociotechnical Implications of RAG for Information Access
Dagstuhl Seminar 25391: Retrieval-Augmented Generation – The Future of Search?
Wadern, Germany, September 2025
SlideShare | PPT
Emancipatory Information Retrieval
People and Technology Lab (PATLab), University College Cork
Virtual, March 2025
SlideShare | PPT | Recording
Sociotechnical Implications of Generative AI for Information Access
(Re)defining Responsible AI workshop, MILA
Montreal, Canada, October 2024
SlideShare | PPT
Bias and Beyond: On Generative AI and the Future of Search and Society
The International Workshop on Algorithmic Bias in Search and Recommendation (BIAS), SIGIR
Washington D.C., USA, July 2024
SlideShare | PDF
Search and Society: Reimagining Information Access for Radical Futures
Canadian AI 2024
Guelph, Canada, May 2024
SlideShare | PPT
Joint Multisided Exposure Fairness for Search and Recommendation
SEA: Search Engines Amsterdam
Virtual, January 2023
SlideShare | PPT
What’s next for deep learning for Search?
Etsy
Virtual, November 2022
SlideShare | PPT
So, You Want to Release a Dataset? Reflections on Benchmark Development, Community Building, and Making Robust Scientific Progress
Spotify
Virtual, September 2022
SlideShare | PDF
Efficient Machine Learning and Machine Learning for Efficiency in Information Retrieval
The Workshop on Reaching Efficiency in Neural Information Retrieval (ReNeuIR), SIGIR
Virtual, July 2022
SlideShare | PPT
Multisided Exposure Fairness for Search and Recommendation
Lowe's
Virtual, June 2022
SlideShare | PPT
Neural Learning to Rank
Dayananda Sagar College of Engineering
Virtual, May 2022
SlideShare | PPT
Deep Learning for Effective, Exposure-Aware, and Efficient Information Retrieval
Microsoft Research Cambridge
Virtual, April 2022
Multisided Exposure Fairness for Search and Recommendation
Microsoft Research Montreal
Virtual, February 2022
Neural Information Retrieval: In search of meaningful progress
CIIR Talk Series, University of Massachusetts Amherst
Virtual, March 2021
Details | SlideShare | PPT | Recording
Neural Information Retrieval: In search of meaningful progress
CLIP Colloquium, University of Maryland
Virtual, March 2021
Details | SlideShare | PPT
Deep Neural Methods for Retrieval
University College London
Virtual, March 2021
SlideShare | PPT
Neural Learning to Rank
University College London
Virtual, March 2021
SlideShare | PPT
Benchmarking for Neural Information Retrieval: MS MARCO, TREC, and Beyond
NLIWOD workshop, International Semantic Web Conference
Virtual, November 2020
SlideShare | PPT
Deep Neural Methods for Retrieval
Emory University
Virtual, April 2020
SlideShare | PPT | Recording
Neural Learning to Rank
Emory University
Virtual, April 2020
SlideShare | PPT | Recording
Learning to Rank for Information Retrieval with Neural Networks
ACM SIGIR/SIGKDD Africa Summer School on Machine Learning for Data Mining and Search (AFIRM)
Cape Town, South Africa, January 2020
SlideShare | PPT | Recording | Hands-on lab materials
Deep Learning for Search
ACM SIGIR/SIGKDD Africa Summer School on Machine Learning for Data Mining and Search (AFIRM)
Cape Town, South Africa, January 2019
SlideShare | PPT | Hands-on lab materials
5 Lessons Learned from Designing Neural Models for Information Retrieval
The 10th Recherche d’Information SEmantique (RISE) workshop, The CORIA-TALN-RJC conference
Rennes, France, May 2018
SlideShare | PPT
A Simple Introduction to Neural Information Retrieval
University College London
London, UK, March 2018
SlideShare | PPT
Neural Models for Information Retrieval
Facebook
Seattle, USA, November 2017
SlideShare | PPT
Neural Models for Information Retrieval
Microsoft Research Redmond
Redmond, USA, November 2017
SlideShare | PPT | Recording
Neural Models for Information Retrieval
School of Computing Sciences, University of Glasgow
Glasgow, UK, November 2017
SlideShare | PPT
Neural Models for Document Ranking
The 4th International Alexandria Workshop
Hannover, Germany, October 2017
SlideShare | PPT
Neural Models for Information Retrieval
The NLIP seminar series, University of Cambridge computer laboratory
Cambridge, UK, October 2017
SlideShare | PPT
Using Text Embeddings for Information Retrieval
School of Computing Sciences, University of Glasgow
Glasgow, UK, May 2016
SlideShare | PPT
A Simple Introduction to Word Embeddings
North Eastern University
Seattle, USA, April 2016
SlideShare | PPT
Vectorland: Brief Notes from Using Text Embeddings for Search
Search Solutions
London, UK, November 2015
SlideShare | PPT
Invited panels
Global South in AI Governance
With Cecil Abungu and Jonas Kgomo
Next Gen AI Forum: Preparing for Tomorrow's AI Governance Today (A Pre-Summit Convening for the India AI Impact Summit 2026), McGill
Organized by Encode Canada
Montréal, Canada, January 2026
AI Ethics and the Tech Industry
With Stefania Pecore, Florian Carichon, and Lilia Jemai
McGill University
Organized by McGill Computer Science Undergraduate Society (CSUS) and Encode Canada
Montréal, Canada, November 2025
To Use Generative AI or Not To Use It
With Mia Shah-Dand, Hessie Jones, and Beatriz González Mellídez
Women in AI Ethics Plus (WAIE+) Debate
Online, August 2025
RecordingDiversity, Equity, and Inclusion (DEI) lunch
With Clemencia Siro, Vanessa Murdock, Nicola Ferro, and Doug Oard
SIGIR
Washington D.C., USA, July 2024From Research To Production
With Julia Kiseleva, Craig Macdonald, Radim Řehůřek, and Agnes van Belle
Industry Day, ECIR
Grenoble, France, March 2018
Invited participation
Shared task organization
Workshop organization
- Justice, Emancipation, Democracy, and Information Access (JEDI): The SIGIR Workshop on Resisting Corporate and Authoritarian Capture of Information Access Platforms, SIGIR, July 2026
- VulGen: International Workshop on Vulnerabilities in Generative Systems for Information Retrieval, SIGIR, July 2026
- LLM4Eval: Large Language Model for Evaluation in IR, SIGIR, July 2025
- LLM4Eval: Large Language Model for Evaluation in IR, WSDM, March 2025
- ReNeuIR at SIGIR 2024: The Third Workshop on Reaching Efficiency in Neural Information Retrieval, SIGIR, July 2024
- LLM4Eval: Large Language Model for Evaluation in IR, SIGIR, July 2024
- The Search Futures Workshop, ECIR, March 2024
- HIPstIR 2019: The hip “stick, sand, and paper” retreat on the future of information retrieval, (report), September 2019
- Neu-IR’17: SIGIR 2017 Workshop on Neural Information Retrieval (report), SIGIR, August 2017
- Neu-IR 2016: The SIGIR 2016 Workshop on Neural Information Retrieval (report), SIGIR, July 2016
Tutorial organization
- Learning to Rank for Information Retrieval with Neural Networks (slides + video + hands-on lab materials), ACM SIGIR/SIGKDD Africa Summer School on Machine Learning for Data Mining and Search (AFIRM), January 2020
- Deep Learning for Search (slides), Forum for Information Retrieval Evaluation (FIRE), December 2019
- Neural Learning to Rank (slides), IVADO recommender systems summer school, August 2019
- Deep Learning for Search (slides + hands-on lab materials), ACM SIGIR/SIGKDD Africa Summer School on Machine Learning for Data Mining and Search (AFIRM), January 2019
- Neural Networks for Information Retrieval, ECIR, March 2018
- Neural Networks for Information Retrieval, WSDM, February 2018
- NN4IR: The SIGIR 2017 tutorial on Neural Networks for Information Retrieval, SIGIR, August 2017
- The WSDM 2017 Tutorial on Neural Text Embeddings for Information Retrieval (slides), WSDM, February 2017
Publications
Information Access of the Oppressed: A Problem-Posing Framework for Envisioning Emancipatory Information Access Platforms ✊🏽✊🏾✊🏼
Bhaskar Mitra, Nicola Neophytou, and Sireesh Gururaja
Preprint, 2026
PDF | ArXivHuman-Centred AI Pipelines: Designing a Platform for Engaging Communities Meaningfully in AI Data Practices to Improve Disability Representation in Image Generation Models
Anja Thieme, Rita Faia Marques, Martin Grayson, Sidhika Balachandar, Cameron Tyler Cassidy, Madiha Zahrah Choksi, Camilla Longden, Reeda Shimaz Huda, Nicholas Ileve Kalovwe, Christina Mallon, Courtney Mansperger, Daniela Massiceti, Bhaskar Mitra, Ruth Mueni Nzioka, Ioana Tanase, Yuzhe You, and Cecily Morrison
In proc. ACM CHI, 2026Overview of the TREC 2025 Tip-of-the-Tongue Track
Jaime Arguello, Fernando Diaz, Maik Fröebe, To Eun Kim, and Bhaskar Mitra
In proc. Text REtrieval Conference (TREC), 2026
Publication | PDF | ArXivJudging the Judges: A Collection of LLM-Generated Relevance Judgements
Hossein A. Rahmani, Clemencia Siro, Mohammad Aliannejadi, Nick Craswell, Charles L. A. Clarke, Guglielmo Faggioli, Bhaskar Mitra, Paul Thomas, and Emine Yilmaz
Preprint, 2025
PDF | ArXivEmancipatory Information Retrieval
Bhaskar Mitra
In Information Retrieval Research Journal (IRRJ), 2025
Publication | PDF | ArXivSIGIR-AP 2025: Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region
Keping Bi, Qingshan Li, Evangelos Kanoulas, Yadan Luo, and Bhaskar Mitra
ProceedingsRetrieval-Augmented Generation – The Future of Search? (Dagstuhl Perspectives Workshop 25391)
Matthias Hagen, Josiane Mothe, Smaranda Muresan, Martin Potthast, Min Zhang, Benno Stein, Qinqyao Ai, Mohammad Aliannejadi, Liesbeth Allein, Avishek Anand, Sophia Althammer, Nolwenn Bernard, Arjen P. de Vries, Niklas Deckers, Gianluca Demartini, Laura Dietz, Carsten Eickhoff, Maik Fröbe, Norbert Fuhr, Marcel Gohsen, Michael Granitzer, Faegheh Hasibi, Sebastian Heineking, Djoerd Hiemstra, Adam Jatowt, Abhinav Joshi, Johannes Kiesel, Wojciech Kusa, Sean MacAvaney, Bhaskar Mitra, Jian-Yun Nie, Heather O’Brien, Birte Platow, Mark Sanderson, Harrisen Scells, Damiano Spina, Benno Stein , Johanne Trippas, Stefan Voigt, and Guido Zuccon
Dagstuhl Reports (to appear), 2025
PDFACM SIGIR Annual Business Meeting 2025: Secretary’s Notes
Bhaskar Mitra
In ACM SIGIR Forum (to appear), 2025
PDFTowards Understanding Bias in Synthetic Data for Evaluation
Hossein A. Rahmani, Varsha Ramineni, Nick Craswell, Bhaskar Mitra, and Emine Yilmaz
In proc. ACM CIKM, 2025
Publication | PDF | ArXivReport from the Fourth Strategic Workshop on Information Retrieval in Lorne (SWIRL 2025)
Johanne R. Trippas, J. Shane Culpepper, Mohammad Aliannejadi, James Allan, Enrique Amigó, Jaime Arguello, Leif Azzopardi, Peter Bailey, Jamie Callan, Rob Capra, Nick Craswell, Bruce Croft, Jeff Dalton, Gianluca Demartini, Laura Dietz, Zhicheng Dou, Carsten Eickhoff, Michael Ekstrand, Nicola Ferro, Norbert Fuhr, Dorota Glowacka, Faegheh Hasibi, Danula Hettiachchi, Rosie Jones, Jaap Kamps, Noriko Kando, Sarvnaz Karimi, Makoto P Kato, Bevan Koopman, Yiqun Liu, Chenglong Ma, Joel Mackenzie, Maria Maistro, Jiaxin Mao, Dana McKay, Bhaskar Mitra, Stefano Mizzaro, Alistair Moffat, Josiane Mothe, Iadh Ounis, Lida Rashidi, Yongli Ren, Mark Sanderson, Rodrygo Santos, Falk Scholer, Chirag Shah, Laurianne Sitbon, Ian Soboroff, Damiano Spina, Paul Thomas, Juli´an Urbano, Arjen de Vries, Ryen White, Abby Yuan, Hamed Zamani, Oleg Zendel, Min Zhang, Justin Zobel, Shengyao Zhuang, and Guido Zuccon
In ACM SIGIR Forum, 2025
Publication | PDFLLM4Eval: Large Language Model for Evaluation in IR
Clemencia Siro, Hossein A. Rahmani, Mohammad Aliannejadi, Nick Craswell, Charles L. A. Clarke, Guglielmo Faggioli, Bhaskar Mitra, Paul Thomas, and Emine Yilmaz
In proc. ACM SIGIR, 2025
Publication | PDFTip of the Tongue Query Elicitation for Simulated Evaluation
Yifan He, To Eun Kim, Fernando Diaz, Jaime Arguello, and Bhaskar Mitra
In proc. ACM SIGIR, 2025
Publication | PDF | ArXivJudgeBlender: Ensembling Automatic Relevance Judgments
Hossein A. Rahmani, Emine Yilmaz, Nick Craswell, and Bhaskar Mitra
In proc. ACM TheWebConf, 2025
Publication | PDF | ArXivSynDL: A Large-Scale Synthetic Test Collection for Passage Retrieval
Hossein A. Rahmani, Xi Wang, Emine Yilmaz, Nick Craswell, Bhaskar Mitra, and Paul Thomas
In proc. ACM TheWebConf, 2025
Publication | PDF | ArXivLLM4Eval@WSDM 2025: Large Language Model for Evaluation in Information Retrieval
Hossein A. Rahmani, Clemencia Siro, Mohammad Aliannejadi, Nick Craswell, Charles L.A. Clarke, Guglielmo Faggioli, Bhaskar Mitra, Paul Thomas, and Emine Yilmaz
In proc. ACM WSDM, 2025
Publication | PDFRecall, Robustness, and Lexicographic Evaluation
Fernando Diaz, Michael D. Ekstrand, and Bhaskar Mitra
In ACM Transactions on Recommender Systems (TORS), 2025
Publication | PDF | ArXivSearch and Society: Reimagining Information Access for Radical Futures
Bhaskar Mitra
In Information Retrieval Research Journal (IRRJ), 2025
Publication | PDF | ArXivSociotechnical Implications of Generative Artificial Intelligence for Information Access
Bhaskar Mitra, Henriette Cramer, and Olya Gurevich
In book "Information Access in the Era of Generative AI" (editors: Chirag Shah and Ryen White), Springer Nature, 2025
Publication | PDF | ArXivOverview of the TREC 2024 Tip-of-the-Tongue Track
Jaime Arguello, Samarth Bhargav, Fernando Diaz, To Eun Kim, Yifan He, Evangelos Kanoulas, and Bhaskar Mitra
In proc. Text REtrieval Conference (TREC), 2025
Publication | PDFThrough the Looking-Glass: Transparency Implications and Challenges in Enterprise AI Knowledge Systems
Karina Cortiñas-Lorenzo, Siân Lindley, Ida Larsen-Ledet, and Bhaskar Mitra
Preprint, 2024
PDF | ArXivResult Diversification in Search and Recommendation: A Survey
Haolun Wu, Yansen Zhang, Chen Ma, Fuyuan Lyu, Bowei He, and Bhaskar Mitra
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024
Publication | PDF | ArXivLLMJudge: LLMs for Relevance Judgments
Hossein A. Rahmani, Emine Yilmaz, Nick Craswell, Bhaskar Mitra, Paul Thomas, Charles L. A. Clarke, Mohammad Aliannejadi, Clemencia Siro, and Guglielmo Faggioli
In proc. LM4Eval: The First Workshop on Large Language Models for Evaluation in Information Retrieval, ACM SIGIR, 2024
Publication | PDF | ArXivProceedings of The First Workshop on Large Language Models for Evaluation in Information Retrieval (LLM4Eval 2024)
Clemencia Siro, Mohammad Aliannejadi, Hossein A. Rahmani, Nick Craswell, Charles L. A. Clarke, Guglielmo Faggioli, Bhaskar Mitra, Paul Thomas, and Emine Yilmaz
ProceedingsReport on the 1st Workshop on Large Language Model for Evaluation in Information Retrieval (LLM4Eval 2024) at SIGIR 2024
Hossein A. Rahmani, Clemencia Siro, Mohammad Aliannejadi, Nick Craswell, Charles L. A. Clarke, Guglielmo Faggioli, Bhaskar Mitra, Paul Thomas, and Emine Yilmaz
In ACM SIGIR Forum, 2024
Publication | PDF | ArXivLLM4Eval: Large Language Model for Evaluation in IR
Hossein A. Rahmani, Clemencia Siro, Mohammad Aliannejadi, Nick Craswell, Charles L. A. Clarke, Guglielmo Faggioli, Bhaskar Mitra, Paul Thomas, and Emine Yilmaz
In proc. ACM SIGIR, 2024
Publication | PDFReNeuIR at SIGIR 2024: The Third Workshop on Reaching Efficiency in Neural Information Retrieval
Maik Fröbe, Joel Mackenzie, Bhaskar Mitra, Franco Maria Nardini, and Martin Potthast
In proc. ACM SIGIR, 2024
Publication | PDFSynthetic Test Collections for Retrieval Evaluation
Hossein A. Rahmani, Nick Craswell, Emine Yilmaz, Bhaskar Mitra, and Daniel Campos
In proc. ACM SIGIR, 2024
Publication | PDF | ArXivLarge Language Models can Accurately Predict Searcher Preferences
Paul Thomas, Seth Spielman, Nick Craswell, and Bhaskar Mitra
In proc. ACM SIGIR, 2024
Publication | PDF | ArXivTowards Group-aware Search Success
Haolun Wu, Bhaskar Mitra, and Nick Craswell
In proc. ACM ICTIR, 2024
Publication | PDF | ArXivLearning to Extract Structured Entities Using Language Models
Haolun Wu, Ye Yuan, Liana Mikaelyan, Alexander Meulemans, Xue Liu, James Hensman, and Bhaskar Mitra
In proc. EMNLP, 2024
Publication | PDF | ArXivA Framework for Exploring the Consequences of AI-Mediated Enterprise Knowledge Access and Identifying Risks to Workers
Anna Gausen, Bhaskar Mitra, and Siân Lindley
In proc. ACM FAccT, 2024
Publication | PDF | ArXivReport on The Search Futures Workshop at ECIR 2024
Leif Azzopardi, Charles L. A. Clarke, Paul Kantor, Bhaskar Mitra, Johanne R. Trippas, and Zhaochun Ren
In ACM SIGIR Forum, 2024
Publication | PDFThe Search Futures Workshop
Leif Azzopardi, Charles L. A. Clarke, Paul B. Kantor, Bhaskar Mitra, Johanne R. Trippas, and Zhaochun Ren
In proc. ECIR, 2024
Publication | PDFOverview of the TREC 2023 Tip-of-the-Tongue Track
Jaime Arguello, Samarth Bhargav, Fernando Diaz, Evangelos Kanoulas, and Bhaskar Mitra
In proc. Text REtrieval Conference (TREC), 2024
Publication | PDFOverview of the TREC 2023 Deep Learning Track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Hossein A. Rahmani, Daniel Campos, Jimmy Lin, Ellen M. Voorhees, and Ian Soboroff
In proc. Text REtrieval Conference (TREC), 2024
Publication | PDF | ArXivProceedings of the 15th annual meeting of the Forum for Information Retrieval Evaluation
Debasis Ganguly, Srijoni Majumdar, Bhaskar Mitra, Parth Gupta, Surupendu Gangopadhyay, and Prasenjit Majumder
ProceedingsDiSK: A Diffusion Model for Structured Knowledge
Ouail Kitouni, Niklas Nolte, James Hensman, and Bhaskar Mitra
Preprint, 2023
PDF | ArXivCo-audit: tools to help humans double-check AI-generated content
Andrew D. Gordon, Carina Negreanu, José Cambronero, Rasika Chakravarthy, Ian Drosos, Hao Fang, Bhaskar Mitra, Hannah Richardson, Advait Sarkar, Stephanie Simmons, Jack Williams, and Ben Zorn
In proc. Workshop on the intersection of HCI and PL (PLATEAU), 2023
Publication | PDF | ArXivPatterns of gender-specializing query reformulation
Amifa Raj, Bhaskar Mitra, Nick Craswell, and Michael Ekstrand
In proc. ACM SIGIR, 2023
Publication | PDF | ArXivDe-Biasing Relevance Judgements for Fair Ranking
Amin Bigdeli, Negar Arabzadeh, Shirin Seyedsalehi, Bhaskar Mitra, Morteza Zihayat, and Ebrahim Bagheri
In proc. ECIR, 2023
Publication | PDFTaking Search to Task
Chirag Shah, Ryen White, Paul Thomas, Bhaskar Mitra, Shawon Sarkar, and Nicholas Belkin
In proc. ACM CHIIR, 2023
Publication | PDF | ArXivOverview of the TREC 2022 Deep Learning Track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, Jimmy Lin, Ellen M. Voorhees, and Ian Soboroff
In proc. Text REtrieval Conference (TREC), 2023
Publication | PDF | ArXivAre We There Yet? A Decision Framework for Replacing Term-Based Retrieval with Dense Retrieval Systems
Sebastian Hofstätter, Nick Craswell, Bhaskar Mitra, Hamed Zamani, and Allan Hanbury
Preprint, 2022
PDF | ArXivEthical and Social Considerations in Automatic Expert Identification and People Recommendation in Organizational Knowledge Management Systems
Ida Larsen-Ledet, Bhaskar Mitra, and Siân Lindley
In proc. FAccTRec Workshop on Responsible Recommendation, ACM RecSys, 2022
PDF | ArXivA Multi-objective Optimization Framework for Multi-stakeholder Fairness-aware Recommendation
Haolun Wu, Chen Ma, Bhaskar Mitra, Fernando Diaz, and Xue Liu
In ACM Transactions on Information Systems (TOIS), 2022
Publication | PDF | ArXivFostering Coopetition While Plugging Leaks: The Design and Implementation of the MS MARCO Leaderboards
Jimmy Lin, Daniel Campos, Nick Craswell, Bhaskar Mitra, and Emine Yilmaz
In proc. ACM SIGIR, 2022
Publication | PDFInconsistent Ranking Assumptions in Medical Search and Their Downstream Consequences
Daniel Cohen, Kevin Du, Bhaskar Mitra, Laura Mercurio, Navid Rekabsaz, and Carsten Eickhoff
In proc. ACM SIGIR, 2022
Publication | PDFJoint Multisided Exposure Fairness for Recommendation
Haolun Wu, Bhaskar Mitra, Chen Ma, Fernando Diaz, and Xue Liu
In proc. ACM SIGIR, 2022
Publication | PDF | ArXivReport on the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021)
Chirag Shah, Torsten Suel, Fernando Diaz, Bhaskar Mitra, Bárbara Poblete, Hussein Suleman, and Suzan Verberne
In ACM SIGIR Forum, 2022
Publication | PDFBias-aware Fair Neural Ranking for Addressing Stereotypical Gender Biases
Shirin SeyedSalehi, Amin Bigdeli, Negar Arabzadeh, Bhaskar Mitra, Morteza Zihayat, and Ebrahim Bagheri
In proc. Extending Database Technology (EDBT), 2022
Publication | PDFExposing Query Identification for Search Transparency
Ruohan Li, Jianxiang Li, Bhaskar Mitra, Fernando Diaz, and Asia J. Biega
In proc. ACM TheWebConf, 2022
Publication | PDF | ArXivLess is Less: When are Snippets Insufficient for Human vs Machine Relevance Estimation?
Gabriella Kazai, Bhaskar Mitra, Anlei Dong, Nick Craswell, and Linjun Yang
In proc. ECIR, 2022
Publication | PDF | ArXivRevisiting Popularity and Demographic Biases in Recommender Evaluation and Effectiveness
Nicola Neophytou, Bhaskar Mitra, and Catherine Stinson
In proc. ECIR, 2022
Publication | PDF | ArXivOverview of the TREC 2021 Deep Learning Track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Jimmy Lin
In proc. Text REtrieval Conference (TREC), 2022
Publication | PDF | ArXivMS MARCO Chameleons: Challenging the MS MARCO Leaderboard with Extremely Obstinate Queries
Negar Arabzadeh, Bhaskar Mitra, and Ebrahim Bagheri
In proc. ACM CIKM, 2021
Publication | PDFIntra-Document Cascading: Learning to Select Passages for Neural Document Ranking
Sebastian Hofstätter, Bhaskar Mitra, Hamed Zamani, Nick Craswell, and Allan Hanbury
In proc. ACM SIGIR, 2021
Publication | PDF | ArXivNot All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models
Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, and Carsten Eickhoff
In proc. ACM SIGIR, 2021
Publication | PDF | ArXivImproving Transformer-Kernel Ranking Model Using Conformer and Query Term Independence
Bhaskar Mitra, Sebastian Hofstätter, Hamed Zamani, and Nick Craswell
In proc. ACM SIGIR, 2021
Publication | PDF | ArXivMS MARCO: Benchmarking Ranking Models in the Large-Data Regime
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Jimmy Lin
In proc. ACM SIGIR, 2021
Publication | PDF | ArXivTREC Deep Learning Track: Reusable Test Collections in the Large Data Regime
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, Ellen M. Voorhees, and Ian Soboroff
In proc. ACM SIGIR, 2021
Publication | PDF | ArXivSignificant Improvements over the State of the Art? A Case Study of the MS MARCO Document Ranking Leaderboard
Jimmy Lin, Daniel Campos, Nick Craswell, Bhaskar Mitra, and Emine Yilmaz
In proc. ACM SIGIR, 2021
Publication | PDF | ArXivTip of the Tongue Known-Item Retrieval: A Case Study in Movie Identification
Jaime Arguello, Adam Ferguson, Emery Fine, Bhaskar Mitra, Hamed Zamani, and Fernando Diaz
In proc. ACM CHIIR, 2021
Publication | PDF | ArXivNeural methods for effective, efficient, and exposure-aware information retrieval
Bhaskar Mitra
In ACM SIGIR Forum, 2021
Publication | PDFNeural Methods for Effective, Efficient, and Exposure-Aware Information Retrieval
Bhaskar Mitra
PhD thesis, University College London, 2021
Publication | PDF | ArXivConformer-Kernel with Query Term Independence at TREC 2020 Deep Learning Track
Bhaskar Mitra, Sebastian Hofstatter, Hamed Zamani, and Nick Craswell
In proc. Text REtrieval Conference (TREC), 2021
Publication | PDF | ArXivOverview of the TREC 2020 Deep Learning Track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos
In proc. Text REtrieval Conference (TREC), 2021
Publication | PDF | ArXivSemantic Product Search for Matching Structured Product Catalogs in E-Commerce
Jason Ingyu Choi, Surya Kallumadi, Bhaskar Mitra, Eugene Agichtein, and Faizan Javed
Preprint, 2020
PDF | ArXivConformer-Kernel with Query Term Independence for Document Retrieval
Bhaskar Mitra, Sebastian Hofstatter, Hamed Zamani, and Nick Craswell
Preprint, 2020
PDF | ArXivEvaluating Stochastic Rankings with Expected Exposure
Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega, and Ben Carterette
In proc. ACM CIKM, 2020
🏆 Best Long Research Paper Nominee
Publication | PDF | ArXivORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search
Nick Craswell, Daniel Campos, Bhaskar Mitra, Emine Yilmaz, and Bodo Billerbeck
In proc. ACM CIKM, 2020
Publication | PDF | ArXivAnalyzing and Learning from User Interactions for Search Clarification
Hamed Zamani, Bhaskar Mitra, Everest Chen, Gord Lueck, Fernando Diaz, Paul N. Bennett, Nick Craswell, and Susan T. Dumais
In proc. ACM SIGIR, 2020
Publication | PDF | ArXivLocal Self-Attention over Long Text for Efficient Document Retrieval
Sebastian Hofstätter, Hamed Zamani, Bhaskar Mitra, Nick Craswell, and Allan Hanbury
In proc. ACM SIGIR, 2020
Publication | PDF | ArXivOn the Reliability of Test Collections for Evaluating Systems of Different Types
Emine Yilmaz, Nick Craswell, Bhaskar Mitra, and Daniel Campos
In proc. ACM SIGIR, 2020
Publication | PDF | ArXivDuet at TREC 2019 Deep Learning Track
Bhaskar Mitra and Nick Craswell
In proc. Text REtrieval Conference (TREC), 2020
Publication | PDF | ArXivOverview of the TREC 2019 Deep Learning Track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M. Voorhees
In proc. Text REtrieval Conference (TREC), 2020
Publication | PDF | ArXivIncorporating Query Term Independence Assumption for Efficient Retrieval and Ranking using Deep Neural Networks
Bhaskar Mitra, Corby Rosset, David Hawking, Nick Craswell, Fernando Diaz, and Emine Yilmaz
Preprint, 2019
PDF | ArXivAn Updated Duet Model for Passage Re-ranking
Bhaskar Mitra and Nick Craswell
Preprint, 2019
PDF | ArXivAn Axiomatic Approach to Regularizing Neural Ranking Models
Corby Rosset, Bhaskar Mitra, Chenyan Xiong, Nick Craswell, Xia Song, and Saurabh Tiwary
In proc. ACM SIGIR, 2019
Publication | PDF | ArXivReport on the First HIPstIR Workshop on the Future of Information Retrieval
Laura Dietz, Bhaskar Mitra, Jeremy Pickens, Hana Anber, Sandeep Avula, Asia Biega, Adrian Boteanu, Shubham Chatterjee, Jeff Dalton, Laura Dietz, Shiri Dori-Hacohen, John Foley, Henry Feild, Ben Gamari, Rosie Jones, Pallika Kanani, Sumanta Kashyapi, Widad Machmouchi, Bhaskar Mitra, Matthew Mitsui, Steve Nole, Alexandre Tachard Passos, Jeremy Pickens, Jordan Ramsdell, Adam Roegiest, David Smith, and Alessandro Sordoni
In ACM SIGIR Forum, 2019
Publication | PDF | ArXivAn Introduction to Neural Information Retrieval
Bhaskar Mitra and Nick Craswell
In Foundations and Trends® in Information Retrieval (FnTIR), 2018
Publication | PDFA Line in the Sand: Recommendation or Ad-hoc Retrieval?
Surya Kallumadi, Bhaskar Mitra, and Tereza Iofciu
ACM RecSys Challenge, 2018
PDF | ArXivCross Domain Regularization for Neural Ranking Models using Adversarial Learning
Daniel Cohen, Bhaskar Mitra, Katja Hofmann, and W. Bruce Croft
In proc. ACM SIGIR, 2018
🏆 Best Short Research Paper Award
Publication | PDF | ArXivOptimizing Query Evaluations Using Reinforcement Learning for Web Search
Corby Rosset, Damien Jose, Gargi Ghosh, Bhaskar Mitra, and Saurabh Tiwary
In proc. ACM SIGIR, 2018
Publication | PDF | ArXivNeural Networks for Information Retrieval
Tom Kenter, Alexey Borisov, Christophe Van Gysel, Mostafa Dehghani, Maarten de Rijke, and Bhaskar Mitra
ECIR, 2018
PDFNeural Networks for Information Retrieval
Tom Kenter, Alexey Borisov, Christophe Van Gysel, Mostafa Dehghani, Maarten de Rijke, and Bhaskar Mitra
ACM WSDM, 2018
PDF | ArXivNeural Ranking Models with Multiple Document Fields
Hamed Zamani, Bhaskar Mitra, Xia Song, Nick Craswell, and Saurabh Tiwary
In proc. ACM WSDM, 2018
Publication | PDF | ArXivNeural Models for Information Retrieval
Bhaskar Mitra and Nick Craswell
Preprint, 2017
PDF | ArXiv | Talk | SlideShare | PPTNeural information retrieval: introduction to the special issue
Nick Craswell, W. Bruce Croft, Maarten de Rijke, Jiafeng Guo, and Bhaskar Mitra
In the special issue of the Information Retrieval Journal (IRJ) on neural information retrieval, Springer Nature, 2017
Publication | PDFLearning to Match using Local and Distributed Representations of Text for Web Search
Bhaskar Mitra, Fernando Diaz, and Nick Craswell
In proc. WWW, 2017
Publication | PDF | ArXivReply With: Proactive Recommendation of Email Attachments
Christophe Van Gysel, Bhaskar Mitra, Matteo Venanzi, Roy Rosemarin, Grzegorz Kukla, Piotr Grudzien, and Nicola Cancedda
In proc. ACM CIKM, 2017
Publication | PDF | ArXivBenchmark for Complex Answer Retrieval
Federico Nanni, Bhaskar Mitra, Matt Magnusson, and Laura Dietz
In proc. ACM ICTIR, 2017
Publication | PDF | ArXivToward Incorporation of Relevant Documents in word2vec
Navid Rekabsaz, Bhaskar Mitra, Mihai Lupu, and Allan Hanbury
In proc. Workshop on Neural Information Retrieval (Neu-IR'17), ACM SIGIR, 2017
PDF | ArXivReport on the Second SIGIR Workshop on Neural Information Retrieval (Neu-IR'17)
Nick Craswell, W. Bruce Croft, Maarten de Rijke, Jiafeng Guo, and Bhaskar Mitra
In ACM SIGIR Forum, 2017
Publication | PDFLuandri: A Clean Lua Interface to the Indri Search Engine
Bhaskar Mitra, Fernando Diaz, and Nick Craswell
In proc. ACM SIGIR, 2017
Publication | PDF | ArXivNeural Networks for Information Retrieval
Tom Kenter, Alexey Borisov, Christophe Van Gysel, Mostafa Dehghani, Maarten de Rijke, and Bhaskar Mitra
In proc. ACM SIGIR, 2017
Publication | PDF | ArXivSIGIR 2017 Workshop on Neural Information Retrieval (Neu-IR'17)
Nick Craswell, W Bruce Croft, Maarten de Rijke, Jiafeng Guo, and Bhaskar Mitra
In proc. ACM SIGIR, 2017
Publication | PDFNeural Text Embeddings for Information Retrieval
Bhaskar Mitra and Nick Craswell
In proc. ACM WSDM, 2017
Publication | PDFReport on the SIGIR 2016 Workshop on Neural Information Retrieval (Neu-IR)
Nick Craswell, W. Bruce Croft, Jiafeng Guo, Bhaskar Mitra, and Maarten de Rijke
In ACM SIGIR Forum, 2016
Publication | PDFNeu-IR: The SIGIR 2016 Workshop on Neural Information Retrieval
Nick Craswell, W. Bruce Croft, Jiafeng Guo, Bhaskar Mitra, and Maarten de Rijke
In proc. ACM SIGIR, 2016
Publication | PDFA Proposal for Evaluating Answer Distillation from Web Data
Bhaskar Mitra, Grady Simon, Jianfeng Gao, Nick Craswell, and Li Deng
In proc. the Second WebQA Workshop, ACM SIGIR, 2016
PDFQuery Expansion with Locally-Trained Word Embeddings
Fernando Diaz, Bhaskar Mitra, and Nick Craswell
In proc. ACL, 2016
Publication | PDF | ArXivA Dual Embedding Space Model for Document Ranking
Bhaskar Mitra, Eric Nalisnick, Nick Craswell, and Rich Caruana
Preprint, 2016
PDF | ArXivImproving Document Ranking with Dual Word Embeddings
Eric Nalisnick, Bhaskar Mitra, Nick Craswell, and Rich Caruana
In proc. WWW, 2016
Publication | PDFQuery Auto-Completion for Rare Prefixes
Bhaskar Mitra and Nick Craswell
In proc. ACM CIKM, 2015
Publication | PDFExploring Session Context using Distributed Representations of Queries and Reformulations
Bhaskar Mitra
In proc. ACM SIGIR, 2015
Publication | PDFAn Introduction to Computational Networks and the Computational Network Toolkit
Amit Agarwal, Eldar Akchurin, Chris Basoglu, Guoguo Chen, Scott Cyphers, Jasha Droppo, Adam Eversole, Brian Guenter, Mark Hillebrand, Xuedong Huang, Zhiheng Huang, Vladimir Ivanov, Alexey Kamenev, Philipp Kranen, Oleksii Kuchaiev, Wolfgang Manousek, Avner May, Bhaskar Mitra, Olivier Nano, Gaizka Navarro, Alexey Orlov, Marko Padmilac, Hari Parthasarathi, Baolin Peng, Alexey Reznichenko, Frank Seide, Michael L. Seltzer, Malcolm Slaney, Andreas Stolcke, Huaming Wang, Kaisheng Yao, Dong Yu, Yu Zhang, and Geoffrey Zweig
Tech report MSR-TR-2014-112, 2014
Publication | PDFAn Eye-tracking Study of User Interactions with Query Auto Completion
Kajta Hofmann, Bhaskar Mitra, Filip Radlinski, and Milad Shokouhi
In proc. ACM CIKM, 2014
Publication | PDFOn user interactions with query auto-completion
Bhaskar Mitra, Milad Shokouhi, Filip Radlinski, and Katja Hofmann
In proc. ACM SIGIR, 2014
Publication | PDF