Yancheng He

488 total citations
16 papers, 167 citations indexed

About

Yancheng He is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics. According to data from OpenAlex, Yancheng He has authored 16 papers receiving a total of 167 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 8 papers in Information Systems and 2 papers in Statistical and Nonlinear Physics. Recurrent topics in Yancheng He's work include Topic Modeling (10 papers), Natural Language Processing Techniques (6 papers) and Web Data Mining and Analysis (5 papers). Yancheng He is often cited by papers focused on Topic Modeling (10 papers), Natural Language Processing Techniques (6 papers) and Web Data Mining and Analysis (5 papers). Yancheng He collaborates with scholars based in China and Canada. Yancheng He's co-authors include Shuqing Bian, Wayne Xin Zhao, Jing Cai, Yunfang Wu, Jingjing Xu, Kun Zhou, Ji-Rong Wen, Xu Sun, Kunfeng Lai and Yu Xu and has published in prestigious journals such as Data Intelligence.

In The Last Decade

Yancheng He

15 papers receiving 163 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yancheng He China 8 114 69 28 14 13 16 167
Sarik Ghazarian United States 6 137 1.2× 93 1.3× 46 1.6× 13 0.9× 13 1.0× 11 202
Enming Yuan China 3 48 0.4× 65 0.9× 15 0.5× 25 1.8× 6 0.5× 4 79
Liangjun Zang China 5 137 1.2× 47 0.7× 37 1.3× 12 0.9× 4 0.3× 17 173
Xin Rong United States 4 46 0.4× 33 0.5× 10 0.4× 12 0.9× 10 0.8× 9 87
Carmine Cesarano Italy 5 226 2.0× 73 1.1× 10 0.4× 17 1.2× 17 1.3× 15 263
Ryohei Sasano Japan 11 282 2.5× 42 0.6× 48 1.7× 11 0.8× 9 0.7× 50 320
Lianzhe Huang China 5 288 2.5× 41 0.6× 27 1.0× 10 0.7× 12 0.9× 5 319
Honglun Zhang China 7 209 1.8× 28 0.4× 47 1.7× 12 0.9× 12 0.9× 11 242
Payal Bajaj United States 6 84 0.7× 27 0.4× 42 1.5× 4 0.3× 8 0.6× 11 127
Jinze Bai China 3 118 1.0× 154 2.2× 50 1.8× 37 2.6× 9 0.7× 4 183

Countries citing papers authored by Yancheng He

Since Specialization
Citations

This map shows the geographic impact of Yancheng He'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 Yancheng He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yancheng He more than expected).

Fields of papers citing papers by Yancheng He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yancheng He. 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 Yancheng He. The network helps show where Yancheng He may publish in the future.

Co-authorship network of co-authors of Yancheng He

This figure shows the co-authorship network connecting the top 25 collaborators of Yancheng He. A scholar is included among the top collaborators of Yancheng He 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 Yancheng He. Yancheng He is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
He, Yancheng, Jiaheng Liu, Weixun Wang, et al.. (2025). Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models. 19182–19208. 1 indexed citations
2.
Liu, Qinrui, et al.. (2025). Bridging the Domain Gap in Grounded Situation Recognition via Unifying Event Extraction across Modalities. Data Intelligence. 7(1). 143–162. 1 indexed citations
3.
Ma, Weizhi, et al.. (2024). Aiming at the Target: Filter Collaborative Information for Cross-Domain Recommendation. 2081–2090. 6 indexed citations
4.
He, Yancheng, Ge Bai, Jie Liu, et al.. (2024). GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models. 12758–12786. 2 indexed citations
5.
He, Yancheng, et al.. (2024). MT-Bench-101: A Fine-Grained Benchmark for Evaluating Large Language Models in Multi-Turn Dialogues. 7421–7454. 10 indexed citations
7.
Wei, Zhongyu, et al.. (2021). Align Voting Behavior with Public Statements for Legislator Representation Learning. 1236–1246. 9 indexed citations
8.
Li, Wei, et al.. (2021). Query-Variant Advertisement Text Generation with Association Knowledge. 412–421. 4 indexed citations
9.
Bian, Shuqing, Wayne Xin Zhao, Kun Zhou, et al.. (2021). Contrastive Curriculum Learning for Sequential User Behavior Modeling via Data Augmentation. 3737–3746. 29 indexed citations
11.
Bian, Shuqing, Wayne Xin Zhao, Kun Zhou, et al.. (2021). A Novel Macro-Micro Fusion Network for User Representation Learning on Mobile Apps. 3199–3209. 7 indexed citations
12.
13.
Xu, Jingjing, et al.. (2019). Coherent Comments Generation for Chinese Articles with a Graph-to-Sequence Model. 4843–4852. 31 indexed citations
14.
Niu, Di, et al.. (2019). A Deep Generative Approach to Search Extrapolation and Recommendation. 1771–1779. 7 indexed citations
15.
He, Yancheng, et al.. (2010). An adaptive affinity propagation document clustering. 1–7. 15 indexed citations
16.
He, Yancheng, et al.. (2010). A Two-layer Text Clustering Approach for Retrospective News Event Detection. 364–368. 7 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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