Chen Lin

Active 1984–2026

Also published as
Chen, Lin
553
Papers
23,860
Citations
76
h-index
287
i10-index

Citations

Citations per year for Chen Lin1940: 1 citations1985: 4 citations1986: 1 citations1987: 1 citations1988: 1 citations1989: 1 citations1990: 1 citations1993: 2 citations1994: 2 citations1996: 1 citations1997: 1 citations1998: 3 citations1999: 5 citations2000: 8 citations2001: 1 citations2002: 3 citations2003: 5 citations2004: 6 citations2005: 8 citations2006: 16 citations2007: 27 citations2008: 36 citations2009: 78 citations2010: 108 citations2011: 131 citations2012: 156 citations2013: 219 citations2014: 263 citations2015: 286 citations2016: 327 citations2017: 358 citations2018: 397 citations2019: 650 citations2020: 849 citations2021: 939 citations2022: 824 citations2023: 941 citations2024: 1,468 citations2025: 1,405 citations2026: 374 citations1941–1984: no citations, so these years are not shown1991–1992: no citations, so these years are not shown1995: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorChina: 3,125 citing papers, 23.9% of this breakdownUnited States: 2,796 citing papers, 21.4% of this breakdownUnited Kingdom: 815 citing papers, 6.2% of this breakdownCanada: 471 citing papers, 3.6% of this breakdownAustralia: 463 citing papers, 3.5% of this breakdownGermany: 457 citing papers, 3.5% of this breakdownFrance: 340 citing papers, 2.6% of this breakdownIndia: 331 citing papers, 2.5% of this breakdownItaly: 312 citing papers, 2.4% of this breakdownSouth Korea: 257 citing papers, 2% of this breakdownHong Kong: 241 citing papers, 1.8% of this breakdownSpain: 237 citing papers, 1.8% of this breakdown
0%23.9%Other 24.8%

Fields

  • Computer Science40.5%
  • Medicine25.3%
  • Biochemistry, Genetics and Molecular Biology8.9%
  • Neuroscience7.8%
  • Engineering5.4%
  • Business, Management and Accounting1.7%
  • Other10.4%

Topics

  • Topic Modeling4%
  • Dementia and Cognitive Impairment Research3.2%
  • Functional Brain Connectivity Studies2.8%
  • Natural Language Processing Techniques2%
  • Machine Learning in Healthcare2%
  • Advanced Neuroimaging Techniques and Applications1.9%
  • Other84.1%

Coauthors

All papers

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  1. The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Robert C. Green, George Bartzokis, Gary H. Glover, John P. Mugler, Michael W. Weiner - Journal of Magnetic Resonance Imaging 2008 cited by 4,381

  2. SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models

    Authors: , , , , , , , , , , , , , , , - arXiv (Cornell University), CoRR 2023 cited by 267

  3. Think-on-Graph: Deep and Responsible Reasoning of Large Language Model with Knowledge Graph

    Authors: , , , , , , , , - ICLR 2024 cited by 303

  4. Rho-1: Not All Tokens Are What You Need

    Authors: , , , , , , , , , , - arXiv (Cornell University), CoRR 2024 cited by 124

  5. Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers

    Authors: , , , , , , , , , , , , , , , , , , , - arXiv (Cornell University), CoRR 2024 cited by 124

  6. AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators

    Authors: , , , , , , , , , - Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track), NAACL (Industry Track) 2024 cited by 136

  7. VLMEvalKit: An Open-Source ToolKit for Evaluating Large Multi-Modality Models

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Dahua Lin, Kai Chen - International Conference on Multimedia, ACM Multimedia 2024 cited by 77

  8. GATraj: A graph- and attention-based multi-agent trajectory prediction model

    Authors: , , , , , - ISPRS Journal of Photogrammetry and Remote Sensing 2023 cited by 90

  9. Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling

    Authors: , , , , , - ICLR 2023 cited by 154

  10. Attacking Recommender Systems with Augmented User Profiles

    Authors: , , , , , - International Conference on Information & Knowledge Management, CIKM 2020 cited by 74

  11. A Novel Group Recommendation Model With Two-Stage Deep Learning

    Authors: , , , , , - IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Trans. Syst. Man Cybern. Syst. 2021 cited by 117

  12. Shilling Black-Box Recommender Systems by Learning to Generate Fake User Profiles

    Authors: , , , , , - IEEE Transactions on Neural Networks and Learning Systems, IEEE Trans. Neural Networks Learn. Syst. 2022 cited by 57

  13. Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records

    Authors: , , , , , , , - Cancer Research 2019 cited by 177

  14. Feature detection and description for image matching: from hand-crafted design to deep learning

    Authors: , , - Geo-spatial Information Science, Geo spatial Inf. Sci. 2020 cited by 96

  15. Graph Inductive Biases in Transformers without Message Passing

    Authors: , , , , , , , - ICML 2023 cited by 208

  16. Regularized Extreme Learning Machine

    Authors: , , - IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 cited by 458

  17. Competition-Level Problems are Effective LLM Evaluators

    Authors: , , , , , , , , , , - Findings of the Association for Computational Linguistics ACL 2024, ACL (Findings) 2024 cited by 27

  18. Making accurate object detection at the edge: review and new approach

    Authors: , , , , , , - Artificial Intelligence Review, Artif. Intell. Rev. 2021 cited by 76

  19. Simplified Modified Rankin Scale Questionnaire

    Authors: , , , , , , , , , , - Stroke 2011 cited by 357

  20. Branched-Chain Amino Acids Exacerbate Obesity-Related Hepatic Glucose and Lipid Metabolic Disorders via Attenuating Akt2 Signaling

    Authors: , , , , , , , , , , , , , , , , , , - Diabetes 2020 cited by 118

  21. Critical downstream analysis steps for single-cell RNA sequencing data

    Authors: , , , , , - Briefings in Bioinformatics, Briefings Bioinform. 2021 cited by 67

  22. Proceedings of the 3rd Clinical Natural Language Processing Workshop

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Julia Ive, Sinead Moylett, Christoph Mueller, Rudolf Cardinal, Sumithra Velupillai, John, O' Brien, Robert Stewart, Wenjie Wang, Youngja Park, Taesung Lee, Ian Molloy, Pengfei Tang, Li Xiong, Elisa Terumi, Rubel Schneider, Joo Vitor Andrioli De Souza, Julien Knafou, Lucas Emanuel Silva E Oliveira, Jenny Copara, Yohan Bonescki Gumiel, Lucas Ferro Antunes De Oliveira, Emerson Cabrera Paraiso, Douglas Teodoro, Cludia Maria, Cabral Moro, Ildiko Pilan, H Pl, Brekke, A Fredrik, Tore Dahl, Haldor Gundersen, Husby, Louise Dupuis, Nicol Bergou, Hegler Tissot, Sumithra Velupillai, Julia Ive, Sinead Moylett, Christoph Mueller, Rudolf Cardinal, Sumithra Velupillai, Danielle Bitterman, Timothy Miller, David Harris, Chen Lin, Sean Finan, Jeremy Warner, Raymond Mak, Guergana Savova, ; Wu, Yu-Cheng Chang, Pin-Jou Lu, Chih-Jen Huang, Yu-Tsang Wang, Hui-Min Hsieh, Kun-San Chao, Tsang-Wu Liu, I-Shou Chang, Yi-Hsin Connie Yang, Ti-Hao Wang, Ko-Jiunn Liu, Li-Tzong Chen, Sheau-Fang Yang 11 ; Chun-Nan, Amilcare Hsu, Gentili, Corey Pharmmt, Xinyan Lester, Yuting Zhao, Yun Ding and 14 more - 2020 cited by 48

  23. Temporal Annotation in the Clinical Domain

    Authors: , , , , , , , , , , - Transactions of the Association for Computational Linguistics, Trans. Assoc. Comput. Linguistics 2014 cited by 247

  24. A comparison of deep learning-based pre-processing and clustering approaches for single-cell RNA sequencing data

    Authors: , , - Briefings in Bioinformatics, Briefings Bioinform. 2021 cited by 43