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Who cites Mark I-Cheng Chen

20,687 citations of their works from 16,629 papers of our library (of the 149,439 whose bibliographies we read) · 3,273 with a page here, the most cited first · page 6 of 33 · 501–600 · ← Mark I-Cheng Chen

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  1. Beyond neural scaling laws: beating power law scaling via data pruningConference on Neural Information Processing Systems (NeurIPS)Ben Sorscher, Robert Geirhos, Shashank Shekhar, et al.2022 · 231 citations
  2. LLaMA-Adapter V2: Parameter-Efficient Visual Instruction ModelarXiv:2304.15010Peng Gao, Jiaming Han, Renrui Zhang, et al.2023 · 229 citations
  3. Progress measures for grokking via mechanistic interpretabilityarXiv:2301.05217Neel Nanda, Lawrence Chan, Tom Lieberum, et al.2023 · 228 citations
  4. Self-critiquing models for assisting human evaluatorsarXiv:2206.05802William Saunders, Catherine Yeh, Jeff Wu, et al.2022 · 228 citations
  5. Qwen2.5-Omni Technical ReportarXiv:2503.20215Jin Xu, Zhifang Guo, Jinzheng He, et al.2025 · 227 citations
  6. MedAlpaca — An Open-Source Collection of Medical Conversational AI Models and Training DataarXiv:2304.08247Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou, et al.2023 · 227 citations
  7. A Survey of Hallucination in Large Foundation ModelsarXiv:2309.05922Vipula Rawte, Amit Sheth, Amitava Das2023 · 226 citations
  8. ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem SolvingarXiv:2309.17452Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 225 citations
  9. Accelerating scientific discovery with Co-ScientistNatureJuraj Gottweis, Wei-Hung Weng, Alexander Daryin, et al.2025 · 224 citations
  10. DataComp: In search of the next generation of multimodal datasetsConference on Neural Information Processing Systems (NeurIPS)Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, et al.2023 · 224 citations
  11. Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought PromptingarXiv:2305.07004Haoyang Huang, Tianyi Tang, Dongdong Zhang, et al.2023 · 224 citations
  12. Reinforced Self-Training (ReST) for Language ModelingarXiv:2308.08998Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.2023 · 224 citations
  13. Specializing Smaller Language Models towards Multi-Step ReasoningarXiv:2301.12726Yao Fu, Hao Peng, Litu Ou, et al.2023 · 224 citations
  14. GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical InformationBioinformaticsQiao Jin, Yifan Yang, Qingyu Chen, et al.2023 · 223 citations
  15. Self-planning Code Generation with Large Language ModelsACM Transactions on Software Engineering and MethodologyXue Jiang, Yihong Dong, Lecheng Wang, et al.2023 · 223 citations
  16. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
  17. Transformer Memory as a Differentiable Search IndexConference on Neural Information Processing Systems (NeurIPS)Yi Tay, Vinh Q. Tran, Mostafa Dehghani, et al.2022 · 223 citations
  18. NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding ModelsarXiv:2405.17428Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.2024 · 222 citations
  19. Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLParXiv:2212.14024Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.2022 · 222 citations
  20. PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about ChangeConference on Neural Information Processing Systems (NeurIPS)Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.2022 · 222 citations
  21. OpenHands: An Open Platform for AI Software Developers as Generalist AgentsarXiv:2407.16741Xingyao Wang, Boxuan Li, Yufan Song, et al.2024 · 221 citations
  22. Med-HALT: Medical Domain Hallucination Test for Large Language ModelsConference on Computational Natural Language Learning (CoNLL)Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu2023 · 221 citations
  23. AlpaGasus: Training A Better Alpaca with Fewer DataarXiv:2307.08701Lichang Chen, Shiyang Li, Jun Yan, et al.2023 · 220 citations
  24. Multilingual Translation from Denoising Pre-TrainingFindings of the Association for Computational LinguisticsYuqing Tang, Chau Tran, Xian Li, et al.2021 · 220 citations
  25. Distilling Reasoning Capabilities into Smaller Language ModelsFindings of the Association for Computational LinguisticsKumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan2023 · 219 citations
  26. Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical ReasoningarXiv:2209.14610Pan Lu, Liang Qiu, Kai-Wei Chang, et al.2022 · 219 citations
  27. FOLIO: Natural Language Reasoning with First-Order LogicarXiv:2209.00840Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.2022 · 219 citations
  28. Maieutic Prompting: Logically Consistent Reasoning with Recursive ExplanationsConference on Empirical Methods in Natural Language Processing (EMNLP)Jaehun Jung, Lianhui Qin, Sean Welleck, et al.2022 · 219 citations
  29. Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language ModelsarXiv:2308.16149Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.2023 · 218 citations
  30. TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question AnsweringIEEE/CVF International Conference on Computer Vision (ICCV)Yushi Hu, Benlin Liu, Jungo Kasai, et al.2023 · 218 citations
  31. Teaching language models to support answers with verified quotesarXiv:2203.11147Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.2022 · 218 citations
  32. Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mosh Levy, Alon Jacoby, Yoav Goldberg2024 · 217 citations
  33. AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent BehaviorsarXiv:2308.10848Weize Chen, Yusheng Su, Jingwei Zuo, et al.2023 · 217 citations
  34. Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4arXiv:2304.03439Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, et al.2023 · 217 citations
  35. Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free LuncharXiv:2311.03099Le Yu, Bowen Yu, Haiyang Yu, et al.2023 · 217 citations
  36. Making Language Models Better Reasoners with Step-Aware VerifierAnnual Meeting of the Association for Computational Linguistics (ACL)Yifei Li, Zeqi Lin, Shizhuo Zhang, et al.2023 · 217 citations
  37. Safe RLHF: Safe Reinforcement Learning from Human FeedbackarXiv:2310.12773Josef Dai, Xuehai Pan, Ruiyang Sun, et al.2023 · 217 citations
  38. Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paperYang Yue, Zhiqi Chen, Rui Lu, et al.2025 · 216 citations
  39. InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal ModelsarXiv:2504.10479Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.2025 · 216 citations
  40. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMatt Deitke, Christopher Clark, Sangho Lee, et al.2024 · 216 citations
  41. LLM+P: Empowering Large Language Models with Optimal Planning ProficiencyarXiv:2304.11477Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.2023 · 216 citations
  42. Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language ModelsFindings of the Association for Computational LinguisticsRobert Logan IV, Ivana Balazevic, Eric Wallace, et al.2022 · 216 citations
  43. MADLAD-400: A Multilingual And Document-Level Large Audited DatasetConference on Neural Information Processing Systems (NeurIPS)Sneha Kudugunta, Isaac Caswell, Biao Zhang, et al.2023 · 213 citations
  44. TinyStories: How Small Can Language Models Be and Still Speak Coherent English?Ronen Eldan, Yuanzhi Li2023 · 213 citations
  45. Demystifying Prompts in Language Models via Perplexity EstimationarXiv:2212.04037Hila Gonen, Srini Iyer, Terra Blevins, et al.2022 · 213 citations
  46. Challenges in Detoxifying Language ModelsFindings of the Association for Computational LinguisticsJohannes Welbl, Amelia Glaese, Jonathan Uesato, et al.2021 · 213 citations
  47. Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLParXiv:2103.00453Timo Schick, Sahana Udupa, Hinrich Schutze2021 · 213 citations
  48. Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine TranslationarXiv:2401.08417Haoran Xu, Amr Sharaf, Yunmo Chen, et al.2024 · 212 citations
  49. What matters when building vision-language models?Conference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.2024 · 212 citations
  50. Compressing Context to Enhance Inference Efficiency of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Yucheng Li, Bo Dong, Frank Guerin, et al.2023 · 212 citations
  51. Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!Findings of the Association for Computational LinguisticsYubo Ma, Yixin Cao, Yong Hong, et al.2023 · 212 citations
  52. Ring Attention with Blockwise Transformers for Near-Infinite ContextarXiv:2310.01889Hao Liu, Matei Zaharia, Pieter Abbeel2023 · 212 citations
  53. Sources of Hallucination by Large Language Models on Inference TasksFindings of the Association for Computational LinguisticsNick McKenna, Tianyi Li, Liang Cheng, et al.2023 · 212 citations
  54. Language Models of Code are Few-Shot Commonsense LearnersConference on Empirical Methods in Natural Language Processing (EMNLP)Aman Madaan, Shuyan Zhou, Uri Alon, et al.2022 · 212 citations
  55. Search-o1: Agentic Search-Enhanced Large Reasoning ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.2025 · 211 citations
  56. Scalable Extraction of Training Data from (Production) Language ModelsarXiv:2311.17035Milad Nasr, Nicholas Carlini, Jonathan Hayase, et al.2023 · 211 citations
  57. “Kelly is a Warm Person, Joseph is a Role Model”: Gender Biases in LLM-Generated Reference LettersFindings of the Association for Computational LinguisticsYixin Wan, George Pu, Jiao Sun, et al.2023 · 211 citations
  58. An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-trained Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Nicholas Meade, Elinor Poole-Dayan, Siva Reddy2022 · 211 citations
  59. From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder PipelinearXiv:2406.11939Tianle Li, Wei-Lin Chiang, Evan Frick, et al.2024 · 210 citations
  60. Generating Training Data with Language Models: Towards Zero-Shot Language UnderstandingarXiv:2202.04538Yu Meng, Jiaxin Huang, Yu Zhang, et al.2022 · 210 citations
  61. Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 210 citations
  62. CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLPConference on Empirical Methods in Natural Language Processing (EMNLP)Qinyuan Ye, Bill Yuchen Lin, Xiang Ren2021 · 210 citations
  63. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
  64. SALMONN: Towards Generic Hearing Abilities for Large Language ModelsarXiv:2310.13289Changli Tang, Wenyi Yu, Guangzhi Sun, et al.2023 · 209 citations
  65. Active Example Selection for In-Context LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Yiming Zhang, Shi Feng, Chenhao Tan2022 · 209 citations
  66. Internet-augmented language models through few-shot prompting for open-domain question answeringarXiv:2203.05115Angeliki Lazaridou, Elena Gribovskaya, Wojciech Stokowiec, et al.2022 · 209 citations
  67. What Can Transformers Learn In-Context? A Case Study of Simple Function ClassesConference on Neural Information Processing Systems (NeurIPS)Shivam Garg, Dimitris Tsipras, Percy Liang, et al.2022 · 209 citations
  68. DeepSeek-VL: Towards Real-World Vision-Language UnderstandingarXiv:2403.05525Haoyu Lu, Wen Liu, Bo Zhang, et al.2024 · 208 citations
  69. EAGLE: Speculative Sampling Requires Rethinking Feature UncertaintyarXiv:2401.15077Yuhui Li, Fangyun Wei, Chao Zhang, et al.2024 · 208 citations
  70. On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Nouha Dziri, Sivan Milton, Mo Yu, et al.2022 · 208 citations
  71. Towards a Unified Multi-Dimensional Evaluator for Text GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Ming Zhong, Yang Liu, Da Yin, et al.2022 · 208 citations
  72. Recursively Summarizing Books with Human FeedbackarXiv:2109.10862Jeff Wu, Long Ouyang, Daniel M. Ziegler, et al.2021 · 208 citations
  73. Optimus: Organizing Sentences via Pre-trained Modeling of a Latent SpaceConference on Empirical Methods in Natural Language Processing (EMNLP)Chunyuan Li, Xiang Gao, Yuan Li, et al.2020 · 208 citations
  74. Aya Dataset: An Open-Access Collection for Multilingual Instruction TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.2024 · 207 citations
  75. RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Cheng Niu, Yuanhao Wu, Juno Zhu, et al.2024 · 207 citations
  76. Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2arXiv:2311.10702Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.2023 · 207 citations
  77. LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language ModelsarXiv:2305.13711Yen-Ting Lin, Yun-Nung Chen2023 · 207 citations
  78. NExT-GPT: Any-to-Any Multimodal LLMarXiv:2309.05519Shengqiong Wu, Hao Fei, Leigang Qu, et al.2023 · 207 citations
  79. BLINK: Multimodal Large Language Models Can See but Not PerceiveLecture notes in computer scienceXingyu Fu, Yushi Hu, Bangzheng Li, et al.2024 · 206 citations
  80. Language Model Tokenizers Introduce Unfairness Between LanguagesConference on Neural Information Processing Systems (NeurIPS)Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, et al.2023 · 206 citations
  81. Woodpecker: Hallucination Correction for Multimodal Large Language ModelsScience China Information SciencesShukang Yin, Chaoyou Fu, Sirui Zhao, et al.2023 · 206 citations
  82. Autoformalization with Large Language ModelsarXiv:2205.12615Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.2022 · 204 citations
  83. On the Effectiveness of Adapter-based Tuning for Pretrained Language Model AdaptationAnnual Meeting of the Association for Computational Linguistics (ACL)Ruidan He, Linlin Liu, Hai Ye, et al.2021 · 204 citations
  84. Measuring Multimodal Mathematical Reasoning with MATH-Vision DatasetConference on Neural Information Processing Systems (NeurIPS)Ke Wang, Junting Pan, Weikang Shi, et al.2024 · 203 citations
  85. DyLoRA: Parameter-Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank AdaptationConference of the European Chapter of the Association for Computational Linguistics (EACL)Mojtaba Valipour, Mehdi Rezagholizadeh, Ivan Kobyzev, et al.2023 · 203 citations
  86. mGPT: Few-Shot Learners Go MultilingualarXiv:2204.07580Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, et al.2022 · 203 citations
  87. Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 202 citations
  88. Large Language Model as Attributed Training Data Generator: A Tale of Diversity and BiasConference on Neural Information Processing Systems (NeurIPS)Yue Yu, Yuchen Zhuang, Jieyu Zhang, et al.2023 · 202 citations
  89. Model Tells You What to Discard: Adaptive KV Cache Compression for LLMsarXiv:2310.01801Suyu Ge, Yunan Zhang, Liyuan Liu, et al.2023 · 202 citations
  90. RRHF: Rank Responses to Align Language Models with Human Feedback without tearsarXiv:2304.05302Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 201 citations
  91. CTRLsum: Towards Generic Controllable Text SummarizationConference on Empirical Methods in Natural Language Processing (EMNLP)Junxian He, Wojciech Kryscinski, Bryan McCann, et al.2022 · 201 citations
  92. ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree SearchConference on Neural Information Processing Systems (NeurIPS)Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.2024 · 200 citations
  93. A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark DatasetsFindings of the Association for Computational LinguisticsMd Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.2023 · 200 citations
  94. Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuningConference on Empirical Methods in Natural Language Processing (EMNLP)Runxin Xu, Fuli Luo, Zhiyuan Zhang, et al.2021 · 200 citations
  95. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and ValidationArtificial Intelligence ReviewXiaowei Huang, Wenjie Ruan, Wei Huang, et al.2023 · 199 citations
  96. MiniGPT-v2: large language model as a unified interface for vision-language multi-task learningarXiv:2310.09478Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.2023 · 199 citations
  97. Improving Passage Retrieval with Zero-Shot Question GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Devendra Sachan, Mike Lewis, Mandar Joshi, et al.2022 · 199 citations
  98. MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and TextConference on Empirical Methods in Natural Language Processing (EMNLP)Wenhu Chen, Hexiang Hu, Xi Chen, et al.2022 · 199 citations
  99. Position Information in Transformers: An OverviewComputational LinguisticsPhilipp Dufter, Martin Schmitt, Hinrich Schütze2022 · 198 citations
  100. Will we run out of data? Limits of LLM scaling based on human-generated dataarXiv:2211.04325Pablo Villalobos, Anson Ho, Jaime Sevilla, et al.2022 · 198 citations

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