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Who cites Melanie Subbiah

11,345 citations of their works from 11,345 papers of our library (of the 149,439 whose bibliographies we read) · 1,982 with a page here, the most cited first · page 1 of 20 · 1–100 · ← Melanie Subbiah

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  1. An Image is Worth 16x16 Words: Transformers for Image Recognition at ScalearXiv:2010.11929Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, et al.2020 · 23,726 citations
  2. GPT-4 Technical ReportarXiv:2303.08774OpenAI, Josh Achiam, Steven Adler, et al.2023 · 13,036 citations
  3. Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsarXiv:2201.11903Jason Wei, Xuezhi Wang, Dale Schuurmans, et al.2022 · 11,499 citations
  4. Training language models to follow instructions with human feedbackarXiv:2203.02155Long Ouyang, Jeff Wu, Xu Jiang, et al.2022 · 10,224 citations
  5. LLaMA: Open and Efficient Foundation Language ModelsarXiv:2302.13971Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al.2023 · 9,603 citations
  6. Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020Alec Radford, Jong Wook Kim, Chris Hallacy, et al.2021 · 8,767 citations
  7. LoRA: Low-Rank Adaptation of Large Language ModelsarXiv:2106.09685Edward J. Hu, Yelong Shen, Phillip Wallis, et al.2021 · 8,661 citations
  8. ChatGPT for Good? On Opportunities and Challenges of Large Language Models for EducationEnkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, et al.2023 · 7,440 citations
  9. Survey of Hallucination in Natural Language GenerationACM Computing SurveysZiwei Ji, Nayeon Lee, Rita Frieske, et al.2022 · 5,974 citations
  10. Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language ProcessingACM Computing SurveysPengfei Liu, Weizhe Yuan, Jinlan Fu, et al.2021 · 5,423 citations
  11. PaLM: Scaling Language Modeling with PathwaysarXiv:2204.02311Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.2022 · 4,753 citations
  12. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,728 citations
  13. Efficient Memory Management for Large Language Model Serving with PagedAttentionarXiv:2309.06180Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, et al.2023 · 4,531 citations
  14. The Power of Scale for Parameter-Efficient Prompt TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Brian Lester, Rami Al-Rfou, Noah Constant2021 · 4,287 citations
  15. Training Verifiers to Solve Math Word ProblemsarXiv:2110.14168Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, et al.2021 · 3,796 citations
  16. A Survey on Evaluation of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyYupeng Chang, Xu Wang, Jindong Wang, et al.2023 · 3,648 citations
  17. Measuring Massive Multitask Language UnderstandingarXiv:2009.03300Dan Hendrycks, Collin Burns, Steven Basart, et al.2020 · 3,620 citations
  18. HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden UnitsIEEE/ACM Transactions on Audio Speech and Language ProcessingWei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, et al.2021 · 3,458 citations
  19. Qwen3 Technical ReportarXiv:2505.09388An Yang, Anfeng Li, Baosong Yang, et al.2025 · 3,382 citations
  20. A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,231 citations
  21. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  22. Self-Consistency Improves Chain of Thought Reasoning in Language ModelsarXiv:2203.11171Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.2022 · 3,121 citations
  23. Direct Preference Optimization: Your Language Model is Secretly a Reward ModelarXiv:2305.18290Rafael Rafailov, Archit Sharma, Eric Mitchell, et al.2023 · 2,896 citations
  24. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  25. Hierarchical Text-Conditional Image Generation with CLIP LatentsarXiv:2204.06125Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, et al.2022 · 2,713 citations
  26. Scalable Diffusion Models with TransformersIEEE/CVF International Conference on Computer Vision (ICCV)William Peebles, Saining Xie2022 · 2,670 citations
  27. Evaluating Large Language Models Trained on CodearXiv:2107.03374Mark Chen, Jerry Tworek, Heewoo Jun, et al.2021 · 2,659 citations
  28. Visual Instruction TuningarXiv:2304.08485Haotian Liu, Chunyuan Li, Qingyang Wu, et al.2023 · 2,617 citations
  29. ReAct: Synergizing Reasoning and Acting in Language ModelsarXiv:2210.03629Shunyu Yao, Jeffrey Zhao, Dian Yu, et al.2022 · 2,591 citations
  30. Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingarXiv:2205.11487Chitwan Saharia, William Chan, Saurabh Saxena, et al.2022 · 2,533 citations
  31. Sparks of Artificial General Intelligence: Early experiments with GPT-4arXiv:2303.12712Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, et al.2023 · 2,439 citations
  32. Measuring Mathematical Problem Solving With the MATH DatasetarXiv:2103.03874Dan Hendrycks, Collin Burns, Saurav Kadavath, et al.2021 · 2,395 citations
  33. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,269 citations
  34. Flamingo: a Visual Language Model for Few-Shot LearningarXiv:2204.14198Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.2022 · 2,246 citations
  35. BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language ModelsarXiv:2301.12597Junnan Li, Dongxu Li, Silvio Savarese, et al.2023 · 2,219 citations
  36. TruthfulQA: Measuring How Models Mimic Human FalsehoodsAnnual Meeting of the Association for Computational Linguistics (ACL)Stephanie Lin, Jacob Hilton, Owain Evans2022 · 2,088 citations
  37. Toolformer: Language Models Can Teach Themselves to Use ToolsConference on Neural Information Processing Systems (NeurIPS)Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, et al.2023 · 2,065 citations
  38. Making Pre-trained Language Models Better Few-shot LearnersAnnual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Adam Fisch, Danqi Chen2021 · 1,987 citations
  39. Finetuned Language Models Are Zero-Shot LearnersarXiv:2109.01652Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.2021 · 1,954 citations
  40. AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated PromptsConference on Empirical Methods in Natural Language Processing (EMNLP)Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.2020 · 1,909 citations
  41. DeBERTa: Decoding-enhanced BERT with Disentangled AttentionarXiv:2006.03654Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.2020 · 1,828 citations
  42. Pre-trained Models for Natural Language Processing: A SurveyarXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.2020 · 1,759 citations
  43. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
  44. Leveraging Passage Retrieval with Generative Models for Open Domain Question AnsweringConference of the European Chapter of the Association for Computational Linguistics (EACL)Gautier Izacard, Edouard Grave2021 · 1,692 citations
  45. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,669 citations
  46. Competition-Level Code Generation with AlphaCodeScienceYujia Li, David Choi, Junyoung Chung, et al.2022 · 1,564 citations
  47. Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A SurveyACM Computing SurveysBonan Min, Hayley Ross, Elior Sulem, et al.2021 · 1,556 citations
  48. Unifying Large Language Models and Knowledge Graphs: A RoadmapIEEE Transactions on Knowledge and Data EngineeringShirui Pan, Linhao Luo, Yufei Wang, et al.2023 · 1,551 citations
  49. Efficient Transformers: A SurveyACM Computing SurveysYi Tay, Mostafa Dehghani, Dara Bahri, et al.2020 · 1,539 citations
  50. DINOv2: Learning Robust Visual Features without SupervisionarXiv:2304.07193Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.2023 · 1,513 citations
  51. LAION-5B: An open large-scale dataset for training next generation image-text modelsarXiv:2210.08402Christoph Schuhmann, Romain Beaumont, Richard Vencu, et al.2022 · 1,485 citations
  52. GLM: General Language Model Pretraining with Autoregressive Blank InfillingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhengxiao Du, Yujie Qian, Xiao Liu, et al.2022 · 1,455 citations
  53. Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?Conference on Empirical Methods in Natural Language Processing (EMNLP)Sewon Min, Xinxi Lyu, Ari Holtzman, et al.2022 · 1,444 citations
  54. LaMDA: Language Models for Dialog ApplicationsarXiv:2201.08239Romal Thoppilan, Daniel De Freitas, Jamie Hall, et al.2022 · 1,344 citations
  55. DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding SharingarXiv:2111.09543Pengcheng He, Jianfeng Gao, Weizhu Chen2021 · 1,320 citations
  56. RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language ModelsFindings of the Association for Computational LinguisticsSamuel Gehman, Suchin Gururangan, Maarten Sap, et al.2020 · 1,306 citations
  57. The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
  58. What Makes Good In-Context Examples for GPT-3?Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning ArchitecturesJiachang Liu, Dinghan Shen, Yizhe Zhang, et al.2022 · 1,256 citations
  59. Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order SensitivityAnnual Meeting of the Association for Computational Linguistics (ACL)Yao Lu, Max Bartolo, Alastair Moore, et al.2022 · 1,209 citations
  60. Program Synthesis with Large Language ModelsarXiv:2108.07732Jacob Austin, Augustus Odena, Maxwell Nye, et al.2021 · 1,192 citations
  61. A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the UglyarXiv:2312.02003Yifan Yao, Jinhao Duan, Kaidi Xu, et al.2023 · 1,186 citations
  62. Least-to-most prompting enables complex reasoning in large language models2022 · 1,165 citations
  63. MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language ModelsarXiv:2304.10592Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.2023 · 1,141 citations
  64. It's Not Just Size That Matters: Small Language Models Are Also Few-Shot LearnersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Timo Schick, Hinrich Schütze2021 · 1,132 citations
  65. Prompt Programming for Large Language Models: Beyond the Few-Shot ParadigmExtended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA)Laria Reynolds, Kyle McDonell2021 · 1,121 citations
  66. Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve ThemFindings of the Association for Computational LinguisticsMirac Suzgun, Nathan Scales, Nathanael Schärli, et al.2023 · 1,119 citations
  67. InstructBLIP: Towards General-purpose Vision-Language Models with Instruction TuningarXiv:2305.06500Wenliang Dai, Junnan Li, Dongxu Li, et al.2023 · 1,100 citations
  68. Bias and Fairness in Large Language Models: A SurveyComputational LinguisticsIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,082 citations
  69. GPT Understands, TooAI OpenXiao Liu, Yanan Zheng, Zhengxiao Du, et al.2021 · 1,054 citations
  70. Vision-Language Models for Vision Tasks: A SurveyIEEE Transactions on Pattern Analysis and Machine IntelligenceJingyi Zhang, Jiaxing Huang, Sheng Jin, et al.2023 · 1,047 citations
  71. P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.2022 · 1,017 citations
  72. A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language ModelsACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li2024 · 1,010 citations
  73. Solving Quantitative Reasoning Problems with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Aitor Lewkowycz, Anders Andreassen, David Dohan, et al.2022 · 992 citations
  74. FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.2023 · 987 citations
  75. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
  76. Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language ModelsComputational LinguisticsYue Zhang, Yafu Li, Leyang Cui, et al.2023 · 977 citations
  77. Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and BeyondarXiv:2308.12966Jinze Bai, Shuai Bai, Shusheng Yang, et al.2023 · 970 citations
  78. Segment AnythingarXiv:2304.02643Alexander Kirillov, Eric Mintun, Nikhila Ravi, et al.2023 · 960 citations
  79. Out of One, Many: Using Language Models to Simulate Human SamplesarXiv:2209.06899Lisa P. Argyle, Ethan C. Busby, Nancy Fulda, et al.2022 · 957 citations
  80. Extracting Training Data from Large Language ModelsarXiv:2012.07805Nicholas Carlini, Florian Tramer, Eric Wallace, et al.2020 · 955 citations
  81. MMBench: Is Your Multi-modal Model an All-around Player?Lecture notes in computer scienceYuan Liu, Haodong Duan, Yuanhan Zhang, et al.2023 · 942 citations
  82. Do As I Can, Not As I Say: Grounding Language in Robotic AffordancesarXiv:2204.01691Michael Ahn, Anthony Brohan, Noah Brown, et al.2022 · 941 citations
  83. Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language ModelsarXiv:2304.01852 · Meta-Radiology (2023)100,017Yiheng Liu, Tianle Han, Siyuan Ma, et al.2023 · 940 citations
  84. Adapted Large Language Models Can Outperform Medical Experts in Clinical Text SummarizationarXiv:2309.07430 · Nature Medicine, 2024Dave Van Veen, Cara Van Uden, Louis Blankemeier, et al.2023 · 931 citations
  85. C-Pack: Packed Resources For General Chinese EmbeddingsInternational ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)Shitao Xiao, Zheng Liu, Peitian Zhang, et al.2023 · 922 citations
  86. Active Retrieval Augmented GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Zhengbao Jiang, Frank Xu, Luyu Gao, et al.2023 · 872 citations
  87. GPT-NeoX-20B: An Open-Source Autoregressive Language ModelBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsSidney Black, Stella Biderman, Eric Hallahan, et al.2022 · 831 citations
  88. Is ChatGPT a General-Purpose Natural Language Processing Task Solver?Conference on Empirical Methods in Natural Language Processing (EMNLP)Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.2023 · 828 citations
  89. Calibrate Before Use: Improving Few-Shot Performance of Language ModelsarXiv:2102.09690Tony Z. Zhao, Eric Wallace, Shi Feng, et al.2021 · 825 citations
  90. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and BeyondACM Transactions on Knowledge Discovery from DataJingfeng Yang, Hongye Jin, Ruixiang Tang, et al.2023 · 814 citations
  91. XLS-R: Self-supervised Cross-lingual Speech Representation Learning at ScaleInterspeechArun Babu, Changhan Wang, Andros Tjandra, et al.2021 · 807 citations
  92. Can Large Language Models Transform Computational Social Science?Computational LinguisticsCaleb Ziems, William Held, Omar Shaikh, et al.2023 · 790 citations
  93. Explainability for Large Language Models: A SurveyACM Transactions on Intelligent Systems and TechnologyHaiyan Zhao, Hanjie Chen, Fan Yang, et al.2023 · 790 citations
  94. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 786 citations
  95. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 780 citations
  96. STaR: Bootstrapping Reasoning With ReasoningEric Zelikman, Yuhuai Wu, Jesse Mu, et al.2022 · 777 citations
  97. ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical ReasoningFindings of the Association for Computational LinguisticsAhmed Masry, Do Xuan Long, Jia Qing Tan, et al.2022 · 774 citations
  98. Reproducible scaling laws for contrastive language-image learningIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMehdi Cherti, Romain Beaumont, Ross Wightman, et al.2022 · 769 citations
  99. UniXcoder: Unified Cross-Modal Pre-training for Code RepresentationAnnual Meeting of the Association for Computational Linguistics (ACL)Daya Guo, Shuai Lu, Nan Duan, et al.2022 · 769 citations
  100. MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding BenchmarkConference on Neural Information Processing Systems (NeurIPS)Yubo Wang, Xueguang Ma, Ge Zhang, et al.2024 · 761 citations

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