Keping Bi

588 total citations
14 papers, 153 citations indexed

About

Keping Bi is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Keping Bi has authored 14 papers receiving a total of 153 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 7 papers in Information Systems and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Keping Bi's work include Topic Modeling (5 papers), Information Retrieval and Search Behavior (4 papers) and Recommender Systems and Techniques (3 papers). Keping Bi is often cited by papers focused on Topic Modeling (5 papers), Information Retrieval and Search Behavior (4 papers) and Recommender Systems and Techniques (3 papers). Keping Bi collaborates with scholars based in China, United States and United Kingdom. Keping Bi's co-authors include Qingyao Ai, W. Bruce Croft, Yongfeng Zhang, Xu Chen, Yongfeng Zhang, Bruce Croft, Rahul Jha, Aslı Çelikyılmaz, Jiafeng Guo and Chen Wang and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Information Systems and arXiv (Cornell University).

In The Last Decade

Keping Bi

11 papers receiving 143 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Keping Bi China 5 107 93 33 10 8 14 153
Sarik Ghazarian United States 6 137 1.3× 93 1.0× 46 1.4× 11 1.1× 13 1.6× 11 202
Salvatore Romeo Qatar 10 209 2.0× 102 1.1× 47 1.4× 8 0.8× 5 0.6× 16 234
Rolf Jagerman United States 6 93 0.9× 68 0.7× 24 0.7× 8 0.8× 31 3.9× 15 142
Jon Saad-Falcon United States 4 127 1.2× 35 0.4× 52 1.6× 6 0.6× 6 0.8× 9 170
Sue Felshin United States 8 149 1.4× 60 0.6× 15 0.5× 5 0.5× 7 0.9× 20 167
Thibault Formal France 4 162 1.5× 55 0.6× 80 2.4× 12 1.2× 7 0.9× 9 200
Canhui Wang China 5 114 1.1× 88 0.9× 19 0.6× 20 2.0× 5 0.6× 8 174
Prasad Pingali India 11 234 2.2× 55 0.6× 20 0.6× 6 0.6× 7 0.9× 18 248
Xin Rong United States 4 46 0.4× 33 0.4× 10 0.3× 7 0.7× 12 1.5× 9 87
Swarnadeep Saha United States 7 201 1.9× 42 0.5× 35 1.1× 8 0.8× 20 2.5× 14 228

Countries citing papers authored by Keping Bi

Since Specialization
Citations

This map shows the geographic impact of Keping Bi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Keping Bi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keping Bi more than expected).

Fields of papers citing papers by Keping Bi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keping Bi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Keping Bi. The network helps show where Keping Bi may publish in the future.

Co-authorship network of co-authors of Keping Bi

This figure shows the co-authorship network connecting the top 25 collaborators of Keping Bi. A scholar is included among the top collaborators of Keping Bi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Keping Bi. Keping Bi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
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4.
Guo, Jiafeng, Keping Bi, Yixing Fan, et al.. (2024). CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval. ACM Transactions on Information Systems. 43(2). 1–25. 1 indexed citations
5.
Cheng, Xueqi, et al.. (2024). GSM-EL: A Generalizable Symbol-Manipulation Approach for Entity Linking. IEEE Transactions on Knowledge and Data Engineering. 37(3). 1213–1226.
6.
Bi, Keping, et al.. (2024). A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval. 674–682. 1 indexed citations
7.
Bi, Keping, et al.. (2023). Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval. 4300–4304. 1 indexed citations
8.
Bi, Keping, et al.. (2023). L2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations. 183–192. 4 indexed citations
9.
Bi, Keping, et al.. (2023). A Comparative Study of Training Objectives for Clarification Facet Generation. 1–10. 2 indexed citations
10.
Bi, Keping, Rahul Jha, Bruce Croft, & Aslı Çelikyılmaz. (2021). AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization. 12 indexed citations
11.
Ai, Qingyao, Yongfeng Zhang, Keping Bi, & W. Bruce Croft. (2019). Explainable Product Search with a Dynamic Relation Embedding Model. ACM Transactions on Information Systems. 38(1). 1–29. 37 indexed citations
12.
Bi, Keping, et al.. (2019). Leverage Implicit Feedback for Context-aware Product Search. arXiv (Cornell University). 1 indexed citations
13.
Ai, Qingyao, Yongfeng Zhang, Keping Bi, Xu Chen, & W. Bruce Croft. (2017). Learning a Hierarchical Embedding Model for Personalized Product Search. 645–654. 87 indexed citations
14.
Wang, Chen, Keping Bi, Yunhua Hu, Hang Li, & Guihong Cao. (2012). Extracting search-focused key n-grams for relevance ranking in web search. 343–352. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026