Jun Xu

About Jun Xu

Jun Xu, With an exceptional h-index of 38 and a recent h-index of 30 (since 2020), a distinguished researcher at Renmin University of China, specializes in the field of Learning to Rank, Semantic Matching.

His recent articles reflect a diverse array of research interests and contributions to the field:

A Taxation Perspective for Fair Re-ranking

Unifying Bias and Unfairness in Information Retrieval: A Survey of Challenges and Opportunities with Large Language Models

UniSAR: Modeling User Transition Behaviors between Search and Recommendation

To Search or to Recommend: Predicting Open-App Motivation with Neural Hawkes Process

Large Language Models Enhanced Collaborative Filtering

Logic Rules as Explanations for Legal Case Retrieval

On the Decision-Making Abilities in Role-Playing using Large Language Models

FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval

Jun Xu Information

University

Position

Professor Gaoling School of Artificial Intelligence

Citations(all)

8032

Citations(since 2020)

4735

Cited By

5366

hIndex(all)

38

hIndex(since 2020)

30

i10Index(all)

78

i10Index(since 2020)

63

Email

University Profile Page

Google Scholar

Jun Xu Skills & Research Interests

Learning to Rank

Semantic Matching

Top articles of Jun Xu

A Taxation Perspective for Fair Re-ranking

arXiv preprint arXiv:2404.17826

2024/4/27

Unifying Bias and Unfairness in Information Retrieval: A Survey of Challenges and Opportunities with Large Language Models

2024/4/17

UniSAR: Modeling User Transition Behaviors between Search and Recommendation

arXiv preprint arXiv:2404.09520

2024/4/15

To Search or to Recommend: Predicting Open-App Motivation with Neural Hawkes Process

arXiv preprint arXiv:2404.03267

2024/4/4

Large Language Models Enhanced Collaborative Filtering

arXiv preprint arXiv:2403.17688

2024/3/26

Logic Rules as Explanations for Legal Case Retrieval

arXiv preprint arXiv:2403.01457

2024/3/3

On the Decision-Making Abilities in Role-Playing using Large Language Models

arXiv preprint arXiv:2402.18807

2024/2/29

FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval

arXiv preprint arXiv:2402.10628

2024/2/16

Reward Imputation with Sketching for Contextual Batched Bandits

Advances in Neural Information Processing Systems

2024/2/13

List-aware Reranking-Truncation Joint Model for Search and Retrieval-augmented Generation

arXiv preprint arXiv:2402.02764

2024/2/5

UOEP: User-Oriented Exploration Policy for Enhancing Long-Term User Experiences in Recommender Systems

arXiv preprint arXiv:2401.09034

2024/1/17

Generative Retrieval with Semantic Tree-Structured Item Identifiers via Contrastive Learning

arXiv preprint arXiv:2309.13375

2023/9/23

Uncovering User Interest from Biased and Noised Watch Time in Video Recommendation

2023/9/14

Uncovering chatgpt’s capabilities in recommender systems

2023/9/14

LTP-MMF: Towards Long-term Provider Max-min Fairness Under Recommendation Feedback Loops

arXiv preprint arXiv:2308.05902

2023/8/11

Law article-enhanced legal case matching: A causal learning approach

2023/7/19

When search meets recommendation: Learning disentangled search representation for recommendation

2023/7/19

P-MMF: Provider Max-min Fairness Re-ranking in Recommender System

2023/4/30

Enhancing Recommendation with Search Data in a Causal Learning Manner

ACM Transactions on Information Systems

2023/4/8

Separating Examination and Trust Bias from Click Predictions for Unbiased Relevance Ranking

2023/2/27

See List of Professors in Jun Xu University(Renmin University of China)

Co-Authors

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