Chenliang Li

7.9k total citations · 2 hit papers
134 papers, 4.5k citations indexed

About

Chenliang Li is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Chenliang Li has authored 134 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 107 papers in Artificial Intelligence, 59 papers in Information Systems and 22 papers in Computer Vision and Pattern Recognition. Recurrent topics in Chenliang Li's work include Topic Modeling (65 papers), Recommender Systems and Techniques (47 papers) and Advanced Graph Neural Networks (35 papers). Chenliang Li is often cited by papers focused on Topic Modeling (65 papers), Recommender Systems and Techniques (47 papers) and Advanced Graph Neural Networks (35 papers). Chenliang Li collaborates with scholars based in China, Singapore and United States. Chenliang Li's co-authors include Aixin Sun, Jing Li, Jianglei Han, Anwitaman Datta, Zongyang Ma, Donghong Ji, Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi and Qiji Zhou and has published in prestigious journals such as International Journal of Molecular Sciences, Frontiers in Immunology and Information Sciences.

In The Last Decade

Chenliang Li

126 papers receiving 4.3k citations

Hit Papers

A Survey on Deep Learning for Named Entity Recognition 2020 2026 2022 2024 2020 2020 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Survey on Deep Learning for Named Entity Recognition
    2020 824 citations Chenliang Li et al. IEEE Transactions on Knowledge and Data Engineering profile →
  2. Adversarial Attacks on Deep-learning Models in Natural Language Processing
    2020 240 citations Wei Emma Zhang, Chenliang Li et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chenliang Li China 32 3.4k 1.5k 595 418 417 134 4.5k
Jiafeng Guo China 36 3.8k 1.1× 1.9k 1.3× 955 1.6× 435 1.0× 525 1.3× 198 5.3k
Yanyan Lan China 25 2.2k 0.6× 1.2k 0.8× 545 0.9× 236 0.6× 288 0.7× 107 3.3k
Fuzheng Zhang China 22 3.6k 1.1× 3.0k 2.0× 852 1.4× 568 1.4× 323 0.8× 52 4.7k
Yaliang Li United States 33 3.2k 0.9× 1.3k 0.9× 426 0.7× 484 1.2× 152 0.4× 144 4.3k
Le Wu China 31 2.4k 0.7× 2.3k 1.5× 757 1.3× 305 0.7× 270 0.6× 117 3.7k
Craig Macdonald United Kingdom 33 2.6k 0.8× 2.8k 1.9× 710 1.2× 352 0.8× 363 0.9× 239 4.4k
Zhoujun Li China 40 3.5k 1.0× 1.3k 0.9× 1.1k 1.9× 205 0.5× 548 1.3× 338 5.2k
Meng Jiang United States 31 2.2k 0.6× 1.2k 0.8× 404 0.7× 180 0.4× 615 1.5× 127 3.5k
Xiang Ren United States 35 4.1k 1.2× 767 0.5× 826 1.4× 384 0.9× 445 1.1× 177 5.0k
Kuansan Wang United States 23 2.0k 0.6× 960 0.6× 502 0.8× 240 0.6× 479 1.1× 65 3.1k

Countries citing papers authored by Chenliang Li

Since Specialization
Citations

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

Fields of papers citing papers by Chenliang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chenliang Li

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

All Works

20 of 20 papers shown
1.
Li, Zihao, Lixin Zou, Chao Ma, & Chenliang Li. (2025). Efficient and explainable sequential recommendation with language model. Information Processing & Management. 62(4). 104122–104122. 1 indexed citations
2.
Zou, Lixin, et al.. (2025). Weak-to-Strong Honesty Alignment via Learning-to-Rank Supervision. 10154–10168.
3.
Ai, Qingyao, et al.. (2025). Structure-Aware Conversational Legal Case Retrieval. ACM Transactions on Information Systems. 43(3). 1–28.
4.
Zhang, Xiaokun, Bo Xu, Chenliang Li, et al.. (2025). A Survey on Side Information-Driven Session-Based Recommendation: From a Data-Centric Perspective. IEEE Transactions on Knowledge and Data Engineering. 37(8). 4411–4431.
5.
Ma, Jiangtao, Бо Лю, Kunlin Li, et al.. (2024). A review of graph neural networks and pretrained language models for knowledge graph reasoning. Neurocomputing. 609. 128490–128490. 8 indexed citations
6.
Ma, Jiangtao, Kunlin Li, Yanjun Wang, et al.. (2024). BGAT-CCRF: A novel end-to-end model for knowledge graph noise correction. Neural Networks. 180. 106715–106715. 1 indexed citations
7.
Shen, Weizhou, Chenliang Li, Ming Yan, et al.. (2024). Small LLMs Are Weak Tool Learners: A Multi-LLM Agent. 16658–16680. 11 indexed citations
8.
Zhang, Wei Emma, et al.. (2024). Disentangle interest trend and diversity for sequential recommendation. Information Processing & Management. 61(3). 103619–103619. 17 indexed citations
9.
Zou, Lixin, et al.. (2024). Unbiased Learning-to-Rank Needs Unconfounded Propensity Estimation. 1535–1545. 1 indexed citations
10.
Zou, Lixin, et al.. (2024). Toward Bias-Agnostic Recommender Systems: A Universal Generative Framework. ACM Transactions on Information Systems. 42(6). 1–30. 4 indexed citations
11.
Tang, Min, et al.. (2024). Sequential recommendation by reprogramming pretrained transformer. Information Processing & Management. 62(1). 103938–103938. 5 indexed citations
12.
Qiao, Yaqiong, Xiangyang Luo, Jiangtao Ma, Meng Zhang, & Chenliang Li. (2023). Twitter user geolocation based on heterogeneous relationship modeling and representation learning. Information Sciences. 647. 119427–119427. 1 indexed citations
13.
Sun, Ke, Tieyun Qian, Chenliang Li, et al.. (2023). Pre-Training Across Different Cities for Next POI Recommendation. ACM Transactions on the Web. 17(4). 1–27. 5 indexed citations
14.
Wang, Pengfei, et al.. (2023). Tutorial: Data Denoising Metrics in Recommender Systems. 5224–5227. 2 indexed citations
15.
Wang, Yanling, et al.. (2023). Poisoning Self-supervised Learning Based Sequential Recommendations. 300–310. 8 indexed citations
16.
Zhang, Xiaokun, Bo Xu, Fenglong Ma, et al.. (2023). Beyond Co-Occurrence: Multi-Modal Session-Based Recommendation. IEEE Transactions on Knowledge and Data Engineering. 36(4). 1450–1462. 22 indexed citations
17.
Zhang, Xiaokun, Bo Xu, Fenglong Ma, et al.. (2023). Bi-preference Learning Heterogeneous Hypergraph Networks for Session-based Recommendation. ACM Transactions on Information Systems. 42(3). 1–28. 11 indexed citations
18.
Ai, Qingyao, et al.. (2023). Leveraging Event Schema to Ask Clarifying Questions for Conversational Legal Case Retrieval. 1513–1522. 4 indexed citations
19.
Wang, Lin, et al.. (2023). Towards Multi-Interest Pre-training with Sparse Capsule Network. 311–320. 10 indexed citations
20.
Tang, Hao, Donghong Ji, Chenliang Li, & Qiji Zhou. (2020). Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification. 6578–6588. 232 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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