Inforrmation Retrieval; Retrieval Augmented Generation; Natural Language Processing

I'm recruiting self-motivated master students who are interested in conducting innovative research. Undergraduate students who are willing to pursue a Ph.D. or master degree in Institute of Computing Technology CAS or abroad are welcome to do internships in my group. If you are interested, please send your resume to my email address and include your research interests and your future plan. 

​

I earned my Ph.D. from the College of Information and Computer Sciences at the University of Massachusetts (UMass) Amherst, under the guidance of Professor W. Bruce Croft at the Center for Intelligent Information Retrieval (CIIR). I also hold two master’s degrees—one in computer science from UMass Amherst and another in machine intelligence from Peking University—and a bachelor’s degree in Computer Science from Nankai University.

   

• Microsoft Search Intelligence & Assistant, Applied Scientist II, USA, July 2021 - August 2022
• Baidu Web Search, Senior Research Engineer at Learning to Rank Group, Beijing, China, July 2012 - July 2015

• Keping Bi, Xiaojie Sun, Jiafeng Guo, Xueqi Cheng. Reproducibility Analysis and Enhancements for Multi-Aspect Dense Retriever with Aspect Learning. Proceedings of the 46th European Conference on Information Retrieval (ECIR'24), 2024.

• Xiaojie Sun, Keping Bi, Jiafeng Guo, Sihui Yang, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Xueqi Cheng. A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval.The 17th ACM International Conference on Web Search and Data Mining (WSDM'24), 2024

• Yinqiong Cai, Keping Bi, Yixing Fan, Jiafeng Guo, Wei Chen, Xueqi Cheng. L2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023

• Xiaojie Sun, Keping Bi, Jiafeng Guo, Xinyu Ma, Yixing Fan, Hongyu Shan, Qishen Zhang, Zhongyi Liu. Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023

• Shiyu Ni, Keping Bi, Jiafeng Guo, Xueqi Cheng. A Comparative Study of Training Objectives for Clarification Facet Generation. Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, SIGIR-AP 2023, Beijing, China, November 26-28, 2023

• Keping Bi, Qingyao Ai, W. Bruce Croft. "Asking Clarifying Questions Based on Negative Feedback in Conversational Search.” In the Proceedings of the 7th ACM International Conference on the Theory of Information Retrieval (ICTIR 2021). Virtual Event, Canada. July 11, 2021. 10 pages. [pdf]

• 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 2021). Virtual Event, Canada. July 11-15, 2021, pp. 123–132. [pdf] 

• 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. pp. 2858–2868. [pdf]

• Keping Bi, Rahul Jha, W. Bruce Croft, Asli Celikyilmaz. "ARedSum: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization''. In the Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL'21), Virtual Event, Kyiv, Ukraine, April 19-23, 2021. pp. 281–291 [pdf]

• Rahul Jha, Keping Bi, Yang Li, Mahdi Pakdaman, Asli Celikyilmaz, Ivan Zhibodev, Kieran McDonald. Artemis: A Novel Annotation Methodology for Indicative Single Document Summarization. in Proceedings of the First Workshop on Evaluation and Comparison of NLP Systems (Eval4NLP), pages 69–78, November 20, 2020. [pdf]

• 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, pp. 1521-1524. 2020, Xi'an, China. Acceptance rate=30.2% (153 out of 507) [pdf]

• Keping Bi, Qingyao Ai, Yongfeng Zhang, W. Bruce Croft. "Conversational Product Search Based on Negative Feedback". Accepted in Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM’19), Beijing, China, November 3-7, 2019. pp. 359–368. Acceptance rate=19.4% (~200 out of ~1030) [pdf]

• Keping Bi, Choon Hui Teo, Yesh Dattatreya, Vijai Mohan, W. Bruce Croft. "A Study of Context Dependencies in Multi-page Product Search". Accepted in Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM’19), Beijing, China, November 3-7, 2019, pp. 2333–2336. Acceptance rate=21.3% (~100 out of ~470) [pdf]

• Qingyao Ai, Yongfeng Zhang, Keping Bi, W. Bruce Croft. Explainable Product Search with a Dynamic Relation Embedding Model. Accepted in ACM Transactions on Information Systems (TOIS), 2019. [pdf] [code]

• Keping Bi, Qingyao Ai, W. Bruce Croft, "Revisiting Iterative Relevance Feedback for Document and Passage Retrieval". Presented at SIGIR Workshop on Conversational Interaction Systems (WCIS'19), 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Paris, France, July 21-25, 2019. [pdf] [poster]

• Keping Bi, Choonhui Teo, Yesh Dattatreya, Vijai Mohan and W. Bruce Croft. "Leverage Implicit Feedback for Context-aware Product Search". Presented at the SIGIR 2019 workshop on eCommerce (ECOM’19), 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Paris, France, July 25, 2019. [pdf] [slides] [poster]

• Keping Bi, Qingyao Ai, W. Bruce Croft. "Iterative Relevance Feedback for Answer Passage Retrieval with Passage-level Semantic Match". In Proceedings of the European Conference on Information Retrieval (ECIR'19), Cologne, Germany, April 14-18, 2019, pp. 558-572. Acceptance rate = 23% (39 out of 165) [pdf] [slides]

• Qingyao Ai, Keping Bi, Cheng Luo, Jiafeng Guo, W. Bruce Croft. Unbiased Learning to Rank with Unbiased Propensity Estimation. In Proceedings of the 41st International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR’18), Ann Arbor, Michigan, USA, July 8-12, 2018, pp. 385–394. [pdf] [code] [slides]

• Qingyao Ai, Keping Bi, Jiafeng Guo, W. Bruce Croft. Learning a Deep Listwise Context Model for Ranking Refinement. In Proceedings of the 41st International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR’18), Ann Arbor, Michigan, USA, July 8-12, 2018, pp. 135–144.  [pdf] [code] [slides]

• Qingyao Ai, Yongfeng Zhang, Keping Bi, Xu Chen, W. Bruce Croft. Learning a Hierarchical Embedding Model for Personalized Product Search. In Proceedings of the 40th International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR’17), Japan, Tokyo, August 7-11, 2017, pp. 645–654. [pdf] [code] [data] [slides]

• Chen Wang, Keping Bi, Yunhua Hu, Hang Li, Guihong Cao, "Extracting Search-Focused Key N-Grams for Relevance Ranking in Web Search". In Proceedings of 5th ACM International Conference on Web Search and Data Mining (WSDM'12), pp. 343-352. 2012. [pdf] [slides]