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期刊文章:

[1] Jiafeng Guo, Yinqiong Cai (指導(dǎo)的學(xué)生), Keping Bi, Yixing Fan, Wei Chen, Ruqing Zhang, and Xueqi Cheng. CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval. Accepted by ACM Transactions on Information Systems (TOIS) 2024.

[2] Qingyao Ai, Yongfeng Zhang, Keping Bi, W. Bruce Croft. Explainable Product Search with a Dynamic Relation Embedding Model. In ACM Transactions on Information Systems (TOIS) 38, no. 1, October, 2019.

會(huì)議文章：

[1] Mingkun Zhang(指導(dǎo)的學(xué)生), Keping Bi, Wei Chen, Quanrun Chen, Jiafeng Guo, Xueqi Cheng. CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense. In the proceedings of Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS'24), Dec 10-15, Vancouver, Canada.

[2] Xiaojie Sun (指導(dǎo)的學(xué)生), Keping Bi, Jiafeng Guo Qishen Zhang, Zhongyi Liu, Guannan Zhang, Xueqi Cheng. MURAL:A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval. In Proceedings of the Web Search and Data Mining Conference 2024 (WSDM'24). Merida, Mexico, March 4-8, 2024.

[3] Wanqing Cui(指導(dǎo)的學(xué)生), Keping Bi, Jiafeng Guo, Xueqi Cheng. MORE: Multi-mOdal REtrieval Augmented Generative Commonsense Reasoning. In Findings of the Association for Computational Linguistics (ACL'24), ACL 2024, pp. 1178–1192. Bangkok, Thailand and virtual meeting, August 11-16, 2024.

[4] Shiyu Ni(指導(dǎo)的學(xué)生), Keping Bi, Jiafeng Guo, Xueqi Cheng. When Do LLMs Need Retrieval Augmentation? Mitigating LLMs' Overconfidence Helps Retrieval Augmentation. In? Findings of the Association for Computational Linguistics (ACL'24), ACL 2024, pp. 11375–11388. Bangkok, Thailand, and virtual meeting, August 11-16, 2024.

[5] Sihui Yang(指導(dǎo)的學(xué)生), Keping Bi, Wanqing Cui, Jiafeng Guo, Xueqi Cheng. LINKAGE: Listwise Ranking among Varied-Quality References for Non-Factoid QA Evaluation via LLMs. In Findings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP'24). Miami, Florida, Nov 12-16, 2024.

[6] Yinqiong Cai (指導(dǎo)的學(xué)生), Keping Bi, Yixing Fan, Jiafeng Guo, Wei Chen, and Xueqi Cheng. L2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM'23), pp. 183-192. Birmingham, United Kingdom, October 21-25, 2023.

[7] Keping Bi, Pavel Metrikov, Chunyuan Li, Byungki Byun. Leveraging User Behavior History for Personalized Email Search. In Proceedings of the Web Conference 2021 (WWW’21). April 19–23, 2021, Ljubljana, Slovenia.

[8] Keping Bi, Qingyao Ai, W. Bruce Croft. Learning a Fine-Grained Review-based Transformer Model for Personalized Product Search. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21). Virtual Event, Canada. July 11-15, 2021.

[9] Keping Bi, Qingyao Ai, W. Bruce Croft. A Transformer-based Embedding Model for Personalized Product Search. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'20). Virtual Event, Xi'an, China, July, 2020.

[10] Keping Bi, Qingyao Ai, Yongfeng Zhang, W. Bruce Croft. Conversational Product Search Based on Negative Feedback. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM'19), Beijing, China, November 3-7, 2019.

[1] 國家青年人才項(xiàng)目：可信賴的智能交互式信息檢索技術(shù)，項(xiàng)目負(fù)責(zé)人；

[2] 國家自然科學(xué)青年基金：面向結(jié)構(gòu)化信息的智能可信的檢索技術(shù)，項(xiàng)目負(fù)責(zé)人；

百度最高獎(jiǎng)提名

計(jì)算技術(shù)研究所新百星