Publications
(* Equal contribution. † Corresponding author.)
| EMNLP 2025 | Similarity = Value? Consultation Value Assessment and Alignment forPersonalized Search Weicong Qin, Yi Xu, Weijie Yu†, Teng Shi, Chenglei Shen, Ming He†, Jianping Fan, Xiao Zhang, Jun Xu [Paper] | 
| EMNLP 2025 | Legal Mathematical Reasoning with LLMs: Procedural Alignment throughTwo-Stage Reinforcement Learning Kepu Zhang, Guofu Xie, Weijie Yu†, Mingyue Xu, Xu Tang, Yaxin Li, Jun Xu [Paper] | 
| EMNLP 2025 | Beyond Guilt: Legal Judgment Prediction with Trichotomous Reasoning Kepu Zhang, Haoyue Yang, Xu Tang, Weijie Yu†, Jun Xu [Paper] | 
| CIKM 2025 | SyLeR: A Framework for Explicit Syllogistic Legal Reasoning in Large Language Models Kepu Zhang, Weijie Yu†, Zhongxiang Sun, Jun Xu [Paper] | 
| CIKM 2025 | PrLM: Learning Explicit Reasoning for Personalized RAG via Contrastive Reward Optimization Kepu Zhang, Teng Shi, Weijie Yu†, Jun Xu [Paper] | 
| CIKM 2025 | Benefit from Rich: Tackling Search Interaction Sparsity in Search Enhanced Recommendation Teng Shi, Weijie Yu†, Xiao Zhang, Ming He, Jianping Fan, Jun Xu [Paper] | 
| RecSys 2025 | MoRE: A Mixture of Reflectors Framework for Large Language Model-Based Sequential Recommendation Weicong Qin, Yi Xu, Weijie Yu†, Chenglei Shen, Xiao Zhang, Ming He, Jianping Fan, Jun Xu [Paper] | 
| RecSys 2025 | Paragon: Parameter Generation for Controllable  Multi-Task Recommendation Chenglei Shen, Jiahao Zhao, Xiao Zhang, Weijie Yu, Ming He, Jianping Fan [Paper] | 
| ACL 2025 | MAPS: Motivation-Aware Personalized Search via LLM-Driven Consultation Alignment Weicong Qin, Yi Xu, Weijie Yu†, Chenglei Shen, Ming He†, Jianping Fan, Xiao Zhang, Jun Xu [Paper] [Code] | 
| ACL 2025 | CitaLaw: Enhancing LLM with Citations in Legal Domain Kepu Zhang, Weijie Yu†, Sunhao Dai, Jun Xu [Paper] | 
| SIGIR 2025 | ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding Zhongxiang Sun, Qipeng Wang, Weijie Yu, Xiaoxue Zang, Kai Zheng, Jun Xu, Xiao Zhang, Song Yang, Han Li [Paper] | 
| Information Sciences | Uncertainty-aware evidential learning for legal case retrieval with noisy correspondence Weicong Qin, Weijie Yu†, Kepu Zhang, Haiyuan Zhao, Jun Xu, Ji-Rong Wen [Paper] | 
| ICLR 2025 | Redeep: Detecting hallucination in retrieval-augmented generation via mechanistic interpretability Zhongxiang Sun, Xiaoxue Zang, Kai Zheng, Yang Song, Jun Xu, Xiao Zhang, Weijie Yu, Han Li [Paper] | 
| COLING 2024 | Logic rules as explanations for legal case retrieval Zhongxiang Sun, Kepu Zhang, Weijie Yu†, Haoyu Wang, Jun Xu [Paper] | 
| SIGIR 2024 | Explicitly Integrating Judgment Prediction with Legal Document Retrieval: A Law-Guided Generative Approach Weicong Qin, Zelin Cao, Weijie Yu, Zihua Si, Sirui Chen, Jun Xu [Paper] | 
| SIGIR 2024 | Reinforcing Long-Term Performance in Recommender Systems with User-Oriented Exploration Policy Changshuo Zhang, Sirui Chen, Xiao Zhang, Sunhao Dai, Weijie Yu, Jun Xu [Paper] | 
| IEEE TKDE | Explainable legal case matching via graph optimal transport Zhongxiang Sun, Weijie Yu, Zihua Si, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, Ji-Rong Wen [Paper] | 
| RecSys 2023 | Uncovering chatgpt’s capabilities in recommender systems Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang, Jun Xu [Paper] [Code] | 
| COLING 2022 | Optimal partial transport based sentence selection for long-form document matching Weijie Yu, Liang Pang, Jun Xu, Bing Su, Zhenhua Dong, Ji-Rong Wen [Paper] [Code] | 
| SIGIR 2022 | Explainable legal case matching via inverse optimal transport-based rationale extraction Weijie Yu, Zhongxiang Sun, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, Ji-Rong Wen [Paper] [Code] | 
| ACM/IEEE TASLP | Distribution distance regularized sequence representation for text matching in asymmetrical domains Weijie Yu, Chen Xu, Jun Xu, Liang Pang, Ji-Rong Wen [Paper] | 
| EMNLP 2020 | Wasserstein distance regularized sequence representation for text matching in asymmetrical domains Weijie Yu, Chen Xu, Jun Xu, Liang Pang, Xiaopeng Gao, Xiaozhao Wang, Ji-Rong Wen [Paper] | 
