| Text matching as image recognition L Pang, Y Lan, J Guo, J Xu, S Wan, X Cheng Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 647 | 2016 |
| A deep architecture for semantic matching with multiple positional sentence representations S Wan, Y Lan, J Guo, J Xu, L Pang, X Cheng Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 432 | 2016 |
| A deep look into neural ranking models for information retrieval J Guo, Y Fan, L Pang, L Yang, Q Ai, H Zamani, C Wu, WB Croft, X Cheng Information Processing & Management 57 (6), 102067, 2020 | 426 | 2020 |
| DeepRank: A new deep architecture for relevance ranking in information retrieval L Pang, Y Lan, J Guo, J Xu, J Xu, X Cheng Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 261 | 2017 |
| Match-srnn: Modeling the recursive matching structure with spatial rnn S Wan, Y Lan, J Xu, J Guo, L Pang, X Cheng arXiv preprint arXiv:1604.04378, 2016 | 197 | 2016 |
| Recosa: Detecting the relevant contexts with self-attention for multi-turn dialogue generation H Zhang, Y Lan, L Pang, J Guo, X Cheng arXiv preprint arXiv:1907.05339, 2019 | 140 | 2019 |
| SetRank: Learning a permutation-invariant ranking model for information retrieval L Pang, J Xu, Q Ai, Y Lan, X Cheng, J Wen Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 137 | 2020 |
| A Study of MatchPyramid Models on Ad-hoc Retrieval. L Pang, Y Lan, J Guo, J Xu, X Cheng Neu-IR '16 SIGIR Workshop on Neural Information Retrieval, 2016 | 104 | 2016 |
| Beyond factoid QA: effective methods for non-factoid answer sentence retrieval L Yang, Q Ai, D Spina, RC Chen, L Pang, WB Croft, J Guo, F Scholer Advances in Information Retrieval: 38th European Conference on IR Research …, 2016 | 91 | 2016 |
| Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks S Xu, L Pang, H Shen, X Cheng, TS Chua Proceedings of the ACM on Web Conference 2024, 1362-1373, 2024 | 75* | 2024 |
| Matchzoo: A toolkit for deep text matching Y Fan, L Pang, JP Hou, J Guo, Y Lan, X Cheng arXiv preprint arXiv:1707.07270, 2017 | 63 | 2017 |
| Hallucidoctor: Mitigating hallucinatory toxicity in visual instruction data Q Yu, J Li, L Wei, L Pang, W Ye, B Qin, S Tang, Q Tian, Y Zhuang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 52 | 2024 |
| LLMDet: A Third Party Large Language Models Generated Text Detection Tool K Wu, L Pang, H Shen, X Cheng, TS Chua Findings of the Association for Computational Linguistics: EMNLP 2023, 2113-2133, 2023 | 45* | 2023 |
| Adaptive information seeking for open-domain question answering Y Zhu, L Pang, Y Lan, H Shen, X Cheng arXiv preprint arXiv:2109.06747, 2021 | 45 | 2021 |
| Has-qa: Hierarchical answer spans model for open-domain question answering L Pang, Y Lan, J Guo, J Xu, L Su, X Cheng Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6875-6882, 2019 | 45 | 2019 |
| A survey on deep text matching L Pang, YY Lan, J Xu, J Guo, SX Wan, X Cheng Chinese Journal of Computers 40 (4), 985-1003, 2017 | 40* | 2017 |
| Bias and unfairness in information retrieval systems: New challenges in the llm era S Dai, C Xu, S Xu, L Pang, Z Dong, J Xu Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 37* | 2024 |
| Llms may dominate information access: Neural retrievers are biased towards llm-generated texts S Dai, Y Zhou, L Pang, W Liu, X Hu, Y Liu, X Zhang, J Xu arXiv preprint arXiv:2310.20501, 2023 | 33* | 2023 |
| Modeling topical relevance for multi-turn dialogue generation H Zhang, Y Lan, L Pang, H Chen, Z Ding, D Yin arXiv preprint arXiv:2009.12735, 2020 | 33 | 2020 |
| Retrieve only when it needs: Adaptive retrieval augmentation for hallucination mitigation in large language models H Ding, L Pang, Z Wei, H Shen, X Cheng arXiv preprint arXiv:2402.10612, 2024 | 30 | 2024 |
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