| Search-in-the-Chain: Towards Accurate, Credible and Traceable Large Language Models for Knowledge-intensive Tasks S Xu, L Pang, H Shen, X Cheng, T Chua WWW 2024, 2023 | 23* | 2023 |
| Match-Prompt: Improving Multi-task Generalization Ability for Neural Text Matching via Prompt Learning S Xu, L Pang, H Shen, X Cheng CIKM 2022, 2290-2300, 2022 | 17* | 2022 |
| BERM: Training the Balanced and Extractable Representation for Matching to Improve Generalization Ability of Dense Retrieval S Xu, L Pang, H Shen, X Cheng ACL 2023, 2023 | 4 | 2023 |
| List-aware Reranking-Truncation Joint Model for Search and Retrieval-augmented Generation S Xu, L Pang, J Xu, H Shen, X Cheng WWW 2024, 2024 | 3 | 2024 |
| Ai-generated images introduce invisible relevance bias to text-image retrieval S Xu, D Hou, L Pang, J Deng, J Xu, H Shen, X Cheng SIGIR 2024, 2023 | 3 | 2023 |
| Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation S Xu, L Pang, M Yu, F Meng, H Shen, X Cheng, J Zhou arXiv preprint arXiv:2402.18150, 2024 | 1 | 2024 |
| Nir-prompt: A multi-task generalized neural information retrieval training framework S Xu, L Pang, H Shen, X Cheng ACM Transactions on Information Systems (TOIS) 42 (2), 1-32, 2023 | 1 | 2023 |
| Plot retrieval as an assessment of abstract semantic association S Xu, L Pang, J Li, M Yu, F Meng, H Shen, X Cheng, J Zhou arXiv preprint arXiv:2311.01666, 2023 | 1 | 2023 |
| Unifying Bias and Unfairness in Information Retrieval: A Survey of Challenges and Opportunities with Large Language Models S Dai, C Xu, S Xu, L Pang, Z Dong, J Xu arXiv preprint arXiv:2404.11457, 2024 | | 2024 |
