Publications

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field.

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Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field.

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1 - 15 of 429 publications
    Information Retrieval and the Web
Permission Rationales in the Web Ecosystem: An Exploration of Rationale Text and Design Patterns
Yusra Elbitar
Soheil Khodayari
Marian Harbach
Gianluca De Stefano
Balazs Engedy
Giancarlo Pellegrino
Sven Bugiel
CHI 2025, ACM
Scaling Up LLM Reviews for Google Ads Content Moderation
Ariel Fuxman
Chih-Chun Chia
Dongjin Kwon
Enming Luo
Mehmet Tek
Ranjay Krishna
Tiantian Fang
Tushar Dogra
Yu-Han Lyu
(2024)
(In)Security of File Uploads in Node.js
Harun Oz
Abbas Acar
Ahmet Aris
Amin Kharraz
Selcuk Uluagac
The Web conference (WWW) (2024)
Beyond Yes and No: Improving Zero-Shot Pointwise LLM Rankers via Scoring Fine-Grained Relevance Labels
Michael Bendersky
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)
Can Query Expansion Improve Generalization of Strong Cross-Encoder Rankers?
Minghan Li
Jimmy Lin
Michael Bendersky
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’24) (2024)
A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models
Shengyao Zhuang
Bevan Koopman
Guido Zuccon
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’24) (2024)
Statistical Analysis of Cardiovascular Diseases Dataset of BRFSS
Ashank Anshuman
Aakarshit Uppal
Indrajit Mukherjee
Open Access Library Journal, 11 (2024)
DSI++: Updating Transformer Memory with New Documents
Yi Tay
Jinfeng Rao
Emma Strubell
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Towards Disentangling Relevance and Bias in Unbiased Learning to Rank
Yunan Zhang
Mike Bendersky
29TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (2023)
Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance
Pratyush Kar
Bing-Rong Lin
Michael Bendersky
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (2023)