2026 Paul N. Bennett: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	50	5614	5456	2562	2474	187	10206

Overview

Paul N. Bennett is affiliated with Microsoft in the United States. Their academic work primarily falls within the field of Computer Science, with a strong emphasis on Artificial Intelligence, supported by 73 publications. Additional subfields include Computer Vision and Pattern Recognition, General Health Professions, Information Systems, and Management Science and Operations Research.

Their research topics cover a broad range of areas, including:

Topic Modeling
Natural Language Processing Techniques
Semantic Web and Ontologies
Speech and dialogue systems
Domain Adaptation and Few-Shot Learning
Multimodal Machine Learning Applications
Advanced Text Analysis Techniques

Paul N. Bennett has contributed to multiple venues, prominently publishing in:

arXiv (Cornell University)
Transactions of the Association for Computational Linguistics
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Findings of the Association for Computational Linguistics: ACL 2022
International Journal of Human-Computer Studies

Selected recent papers include:

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval, 2020, arXiv (Cornell University)
<scp>SummaC</scp>: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization, 2022, Transactions of the Association for Computational Linguistics
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining, 2021, arXiv (Cornell University)
Knowledge-Aware Language Model Pretraining, 2020, arXiv (Cornell University)
Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Their collaborative work includes frequent co-authorship with researchers such as Chenyan Xiong, Jianfeng Gao, Nick Craswell, Philippe Laban, and Tobias Schnabel.

Paul N. Bennett has contributed a book titled Neural Approaches to Conversational Information Retrieval, published in 2023 as part of the "information retrieval series". This work has been cited multiple times within the academic community.

Best Publications

Guidelines for Human-AI Interaction

Saleema Amershi;Dan Weld;Mihaela Vorvoreanu;Adam Fourney

1602
Citations
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Lee Xiong;Chenyan Xiong;Ye Li;Kwok-Fung Tang

397
Citations
Pairwise ranking aggregation in a crowdsourced setting

Xi Chen;Paul N. Bennett;Kevyn Collins-Thompson;Eric Horvitz

391
Citations
Modeling the impact of short- and long-term behavior on search personalization

Paul N. Bennett;Ryen W. White;Wei Chu;Susan T. Dumais

358
Citations
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Lee Xiong;Chenyan Xiong;Ye Li;Kwok-Fung Tang

326
Citations
Here or There

Ben Carterette;Paul N. Bennett;David Maxwell Chickering;Susan T. Dumais

251
Citations
Will You Accept an Imperfect AI?: Exploring Designs for Adjusting End-user Expectations of AI Systems

Rafal Kocielnik;Saleema Amershi;Paul N. Bennett

245
Citations
Dual Strategy Active Learning

Pinar Donmez;Jaime G. Carbonell;Paul N. Bennett

233
Citations
Here or there: preference judgments for relevance

Ben Carterette;Paul N. Bennett;David Maxwell Chickering;Susan T. Dumais

232
Citations
Personalizing web search results by reading level

Kevyn Collins-Thompson;Paul N. Bennett;Ryen W. White;Sebastian de la Chica

216
Citations
Predicting short-term interests using activity-based search context

Ryen W. White;Paul N. Bennett;Susan T. Dumais

214
Citations
Generating Clarifying Questions for Information Retrieval

Hamed Zamani;Susan Dumais;Nick Craswell;Paul Bennett

206
Citations
Modeling and analysis of cross-session search tasks

Alexander Kotov;Paul N. Bennett;Ryen W. White;Susan T. Dumais

187
Citations
Learning to Rank Using an Ensemble of Lambda-Gradient Models

Christopher J. C. Burges;Krysta Marie Svore;Paul N. Bennett;Andrzej Pastusiak

168
Citations
Inferring and using location metadata to personalize web search

Paul N. Bennett;Filip Radlinski;Ryen W. White;Emine Yilmaz

164
Citations
Refined experts: improving classification in large taxonomies

Paul N. Bennett;Nam Nguyen

162
Citations
Redundancy, diversity and interdependent document relevance

Filip Radlinski;Paul N. Bennett;Ben Carterette;Thorsten Joachims

160
Citations
TREC 2014 Web Track Overview

Kevyn Collins-Thompson;Craig Macdonald;Paul N. Bennett;Fernando Diaz

151
Citations
SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization

Philippe Laban;Tobias Schnabel;Paul N. Bennett;Marti A. Hearst

145
Citations
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining

Paul N. Bennett;Vanja Josifovski;Jennifer Neville;Filip Radlinski

51
Citations
TREC 2013 Web Track Overview

Kevyn Collins-Thompson;Paul Bennett;Fernando Diaz;Charles L Clarke

22
Citations
Preference Judgments for Relevance

Ben Carterette;Paul N. Bennett;David Maxwell Chickering;Susan T. Dumais

0
Citations

Frequent Co-Authors

Ryen W. White Microsoft (United States)

Susan T. Dumais Microsoft (United States)

Kevyn Collins-Thompson University of Michigan–Ann Arbor

Eric Horvitz Microsoft (United States)

Filip Radlinski Google (United States)

Ben Carterette Spotify, US

David Maxwell Chickering Microsoft (United States)

Thorsten Joachims Cornell University

Krysta M. Svore Microsoft (United States)

Nick Craswell Microsoft (United States)

External Links

Personal website of Paul N. Bennett Google Scholar page

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