Tianlong Chen

4.2k total citations · 1 hit paper
73 papers, 1.1k citations indexed

About

Tianlong Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Tianlong Chen has authored 73 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Artificial Intelligence, 31 papers in Computer Vision and Pattern Recognition and 7 papers in Molecular Biology. Recurrent topics in Tianlong Chen's work include Advanced Neural Network Applications (14 papers), Adversarial Robustness in Machine Learning (10 papers) and Topic Modeling (8 papers). Tianlong Chen is often cited by papers focused on Advanced Neural Network Applications (14 papers), Adversarial Robustness in Machine Learning (10 papers) and Topic Modeling (8 papers). Tianlong Chen collaborates with scholars based in United States, China and Hong Kong. Tianlong Chen's co-authors include Zhangyang Wang, Shaojin Ding, Wuyang Chen, Zhou Ren, Ye Yuan, Yang Yang, Jingyi Xie, Yuning You, Yang Shen and Shiyu Chang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Neurocomputing.

In The Last Decade

Tianlong Chen

59 papers receiving 1.1k citations

Hit Papers

ABD-Net: Attentive but Diverse Person Re-Identification 2019 2026 2021 2023 2019 100 200 300
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. ABD-Net: Attentive but Diverse Person Re-Identification
    2019 360 citations Tianlong Chen 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
Tianlong Chen United States 17 651 533 170 69 60 73 1.1k
Zhenzhong Lan China 13 778 1.2× 551 1.0× 130 0.8× 37 0.5× 78 1.3× 50 1.1k
Xiaoshan Yang China 21 969 1.5× 553 1.0× 62 0.4× 70 1.0× 65 1.1× 84 1.4k
Chaoqun Hong China 13 1.0k 1.6× 417 0.8× 138 0.8× 40 0.6× 86 1.4× 51 1.4k
Peiguang Jing China 16 706 1.1× 296 0.6× 68 0.4× 101 1.5× 65 1.1× 92 1.1k
Yidong Chen China 16 274 0.4× 501 0.9× 65 0.4× 54 0.8× 28 0.5× 99 899
Kaoru Hirota Japan 16 328 0.5× 272 0.5× 58 0.3× 40 0.6× 57 0.9× 76 827
Sung Ju Hwang South Korea 21 834 1.3× 812 1.5× 39 0.2× 48 0.7× 77 1.3× 81 1.4k

Countries citing papers authored by Tianlong Chen

Since Specialization
Citations

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

Fields of papers citing papers by Tianlong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tianlong Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Tianlong Chen. A scholar is included among the top collaborators of Tianlong Chen 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 Tianlong Chen. Tianlong Chen 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.
Wang, Zhangyang, et al.. (2025). MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models. 2858–2873. 3 indexed citations
2.
3.
Qiu, Michael, Xi-Jiang Hu, Fenghuang Zhan, et al.. (2025). GRNFormer: A Biologically-Guided Framework for Integrating Gene Regulatory Networks into RNA Foundation Models. 3805–3819.
4.
Pang, Linsey, Tianlong Chen, Kun Wang, et al.. (2025). A Survey on Trustworthy LLM Agents: Threats and Countermeasures. 6216–6226. 5 indexed citations
5.
Park, Daniel, et al.. (2025). Using large language models to address the bottleneck of georeferencing natural history collections. Nature Plants. 11(12). 2446–2450.
6.
Zhang, Zhenhao, Shirui Pan, Tianlong Chen, et al.. (2025). GatorCLR: Personalized predictions of patient outcomes on electronic health records using self-supervised contrastive graph representation. Journal of Biomedical Informatics. 168. 104851–104851.
7.
Jaiswal, Ajay, et al.. (2024). FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. 16943–16956. 1 indexed citations
8.
Wang, Xiangwen, et al.. (2024). Reinforcement Learning-Driven LLM Agent for Automated Attacks on LLMs. 170–177. 2 indexed citations
9.
Chen, Tianlong, et al.. (2024). Sparsity-Guided Holistic Explanation for LLMs with Interpretable Inference-Time Intervention. Proceedings of the AAAI Conference on Artificial Intelligence. 38(19). 21619–21627. 9 indexed citations
10.
Duan, Jinhao, Chenxi Yuan, Qingyu Chen, et al.. (2024). Word-Sequence Entropy: Towards uncertainty estimation in free-form medical question answering applications and beyond. Engineering Applications of Artificial Intelligence. 139. 109553–109553. 2 indexed citations
11.
Nguyen, Nghi, Jingxuan Bao, Alan D. Kaplan, et al.. (2024). A Principled Framework to Assess the Information-Theoretic Fitness of Brain Functional Sub-Circuits. Mathematics. 12(19). 2967–2967. 1 indexed citations
12.
Chen, Tianlong, et al.. (2023). A Novel Semi-Quantum Co-Signature Scheme Based on GHZ States and Four-Particle Cluster States. International Journal of Theoretical Physics. 62(4). 5 indexed citations
13.
Zhang, Zhenyu, et al.. (2023). Accelerable Lottery Tickets with the Mixed-Precision Quantization. 33. 4604–4612. 1 indexed citations
14.
Diaz, Daniel J., et al.. (2023). Two sequence- and two structure-based ML models have learned different aspects of protein biochemistry. Scientific Reports. 13(1). 13280–13280. 6 indexed citations
15.
Chen, Xuxi, et al.. (2023). DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models. 8208–8222. 2 indexed citations
16.
Jiang, Ziyu, Tianlong Chen, Ting Chen, & Zhangyang Wang. (2021). Improving Contrastive Learning on Imbalanced Data via Open-World Sampling. Neural Information Processing Systems. 34. 6 indexed citations
17.
Chen, Jiabo, Tianlong Chen, Bin Xiao, et al.. (2020). SE-ECGNet: Multi-scale SE-Net for Multi-lead ECG Data. Computing in cardiology. 47. 11 indexed citations
18.
Yu, Xiao‐Jing, Tianlong Chen, Huiyu Li, et al.. (2020). Dataset and Enhanced Model for Eligibility Criteria-to-SQL Semantic Parsing. Language Resources and Evaluation. 5829–5837. 3 indexed citations
19.
Chen, Tianlong, et al.. (2020). Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free. arXiv (Cornell University). 33. 7449–7461. 1 indexed citations
20.
You, Yuning, Tianlong Chen, Yongduo Sui, et al.. (2020). Graph Contrastive Learning with Augmentations. Neural Information Processing Systems. 33. 5812–5823. 46 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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