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Who cites Brian Lester

3,479 citations of their works from 3,131 papers of our library (of the 149,439 whose bibliographies we read) · 716 with a page here, the most cited first · page 1 of 8 · 1–100 · ← Brian Lester

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  1. Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsarXiv:2201.11903Jason Wei, Xuezhi Wang, Dale Schuurmans, et al.2022 · 11,499 citations
  2. Training language models to follow instructions with human feedbackarXiv:2203.02155Long Ouyang, Jeff Wu, Xu Jiang, et al.2022 · 10,224 citations
  3. Llama 2: Open Foundation and Fine-Tuned Chat ModelsarXiv:2307.09288Hugo Touvron, Louis Martin, Kevin Stone, et al.2023 · 9,669 citations
  4. LoRA: Low-Rank Adaptation of Large Language ModelsarXiv:2106.09685Edward J. Hu, Yelong Shen, Phillip Wallis, et al.2021 · 8,661 citations
  5. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  6. 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
  7. PaLM: Scaling Language Modeling with PathwaysarXiv:2204.02311Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.2022 · 4,753 citations
  8. Judging LLM-as-a-Judge with MT-Bench and Chatbot ArenaConference on Neural Information Processing Systems (NeurIPS)Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.2023 · 4,573 citations
  9. Efficient Memory Management for Large Language Model Serving with PagedAttentionarXiv:2309.06180Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, et al.2023 · 4,531 citations
  10. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  11. Gemini: A Family of Highly Capable Multimodal ModelsarXiv:2312.11805Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.2023 · 3,050 citations
  12. QLoRA: Efficient Finetuning of Quantized LLMsConference on Neural Information Processing Systems (NeurIPS)Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.2023 · 2,929 citations
  13. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  14. Improved Baselines with Visual Instruction TuningIEEE Computer Society Conference on Computer Vision and Pattern RecognitionHaotian Liu, Chunyuan Li, Yuheng Li, et al.2023 · 2,614 citations
  15. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,269 citations
  16. Flamingo: a Visual Language Model for Few-Shot LearningarXiv:2204.14198Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.2022 · 2,246 citations
  17. TruthfulQA: Measuring How Models Mimic Human FalsehoodsAnnual Meeting of the Association for Computational Linguistics (ACL)Stephanie Lin, Jacob Hilton, Owain Evans2022 · 2,088 citations
  18. Finetuned Language Models Are Zero-Shot LearnersarXiv:2109.01652Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.2021 · 1,954 citations
  19. 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
  20. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
  21. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
  22. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,669 citations
  23. Multitask Prompted Training Enables Zero-Shot Task GeneralizationarXiv:2110.08207Victor Sanh, Albert Webson, Colin Raffel, et al.2021 · 1,612 citations
  24. 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
  25. 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
  26. 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
  27. Code Llama: Open Foundation Models for CodearXiv:2308.12950Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.2024 · 1,430 citations
  28. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
  29. 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
  30. Program Synthesis with Large Language ModelsarXiv:2108.07732Jacob Austin, Augustus Odena, Maxwell Nye, et al.2021 · 1,192 citations
  31. 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
  32. InstructBLIP: Towards General-purpose Vision-Language Models with Instruction TuningarXiv:2305.06500Wenliang Dai, Junnan Li, Dongxu Li, et al.2023 · 1,100 citations
  33. Bias and Fairness in Large Language Models: A SurveyComputational LinguisticsIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,082 citations
  34. GPT Understands, TooAI OpenXiao Liu, Yanan Zheng, Zhengxiao Du, et al.2021 · 1,054 citations
  35. LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.2024 · 1,048 citations
  36. 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
  37. 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
  38. Universal and Transferable Adversarial Attacks on Aligned Language ModelsarXiv:2307.15043Andy Zou, Zifan Wang, Nicholas Carlini, et al.2023 · 1,005 citations
  39. PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 1,000 citations
  40. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
  41. 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
  42. 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
  43. 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
  44. 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
  45. 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
  46. 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
  47. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 786 citations
  48. STaR: Bootstrapping Reasoning With ReasoningEric Zelikman, Yuhuai Wu, Jesse Mu, et al.2022 · 777 citations
  49. HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging FaceConference on Neural Information Processing Systems (NeurIPS)Yongliang Shen, Kaitao Song, Xu Tan, et al.2023 · 756 citations
  50. Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Haokun Liu, Derek Tam, Mohammed Muqeeth, et al.2022 · 754 citations
  51. WizardLM: Empowering large pre-trained language models to follow complex instructionsInternational Conference on Learning Representations (ICLR)Can Xu, Qingfeng Sun, Kai Zheng, et al.2023 · 741 citations
  52. CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model SocietyConference on Neural Information Processing Systems (NeurIPS)Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, et al.2023 · 706 citations
  53. Crosslingual Generalization through Multitask FinetuningarXiv:2211.01786Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.2022 · 703 citations
  54. Large Language Models Are Human-Level Prompt EngineersarXiv:2211.01910Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.2022 · 701 citations
  55. Red Teaming Language Models with Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Ethan Perez, Saffron Huang, Francis Song, et al.2022 · 700 citations
  56. Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model SizesFindings of the Association for Computational LinguisticsCheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.2023 · 690 citations
  57. Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionarXiv:2310.11511Akari Asai, Zeqiu Wu, Yizhong Wang, et al.2023 · 677 citations
  58. Atlas: Few-shot Learning with Retrieval Augmented Language ModelsarXiv:2208.03299Gautier Izacard, Patrick Lewis, Maria Lomeli, et al.2022 · 673 citations
  59. Instruction Tuning with GPT-4arXiv:2304.03277Baolin Peng, Chunyuan Li, Pengcheng He, et al.2023 · 662 citations
  60. Towards a Unified View of Parameter-Efficient Transfer LearningarXiv:2110.04366Junxian He, Chunting Zhou, Xuezhe Ma, et al.2021 · 619 citations
  61. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 618 citations
  62. Instruction-Following Evaluation for Large Language ModelsarXiv:2311.07911Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.2023 · 615 citations
  63. Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language ModelarXiv:2201.11990Shaden Smith, Mostofa Patwary, Brandon Norick, et al.2022 · 615 citations
  64. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 607 citations
  65. ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIsarXiv:2307.16789Yujia Qin, Shihao Liang, Yining Ye, et al.2023 · 589 citations
  66. AudioLM: a Language Modeling Approach to Audio GenerationIEEE/ACM Transactions on Audio Speech and Language ProcessingZalan Borsos, Raphael Marinier, Damien Vincent, et al.2022 · 581 citations
  67. Large Language Models Can Self-ImproveConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Huang, Shixiang Gu, Le Hou, et al.2023 · 575 citations
  68. Galactica: A Large Language Model for SciencearXiv:2211.09085Ross Taylor, Marcin Kardas, Guillem Cucurull, et al.2022 · 570 citations
  69. Precise Zero-Shot Dense Retrieval without Relevance LabelsAnnual Meeting of the Association for Computational Linguistics (ACL)Luyu Gao, Xueguang Ma, Jimmy Lin, et al.2022 · 549 citations
  70. Large Language Models Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
  71. TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with RecommendationarXiv:2305.00447Keqin Bao; Jizhi Zhang; Yang Zhang; Wenjie Wang; Fuli Feng;, Xiangnan He2023 · 531 citations
  72. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  73. Multilingual Machine Translation with Large Language Models: Empirical Results and AnalysisFindings of the Association for Computational LinguisticsWenhao Zhu, Hongyi Liu, Qingxiu Dong, et al.2024 · 506 citations
  74. Sentiment Analysis in the Era of Large Language Models: A Reality CheckFindings of the Association for Computational LinguisticsWenxuan Zhang, Yue Deng, Bing Liu, et al.2023 · 506 citations
  75. GLaM: Efficient Scaling of Language Models with Mixture-of-ExpertsarXiv:2112.06905Nan Du, Yanping Huang, Andrew M. Dai, et al.2021 · 496 citations
  76. Orca: A Distributed Serving System for Transformer-Based Generative ModelsOSDI 2022Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, et al.2022 · 478 citations
  77. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
  78. PPT: Pre-trained Prompt Tuning for Few-shot LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxian Gu, Xu Han, Zhiyuan Liu, et al.2022 · 471 citations
  79. P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and TasksarXiv:2110.07602Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.2021 · 469 citations
  80. OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning FrameworkarXiv:2202.03052Peng Wang, An Yang, Rui Men, et al.2022 · 467 citations
  81. MVBench: A Comprehensive Multi-modal Video Understanding BenchmarkIEEE Computer Society Conference on Computer Vision and Pattern RecognitionKunchang Li, Yali Wang, Yinan He, et al.2023 · 463 citations
  82. AlpacaFarm: A Simulation Framework for Methods that Learn from Human FeedbackConference on Neural Information Processing Systems (NeurIPS)Yann Dubois, Xuechen Li, Rohan Taori, et al.2023 · 456 citations
  83. Large language models are few-shot clinical information extractorsConference on Empirical Methods in Natural Language Processing (EMNLP)Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.2022 · 454 citations
  84. The Falcon Series of Open Language ModelsarXiv:2311.16867Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.2023 · 443 citations
  85. GPT-NER: Named Entity Recognition via Large Language ModelsFindings of the Association for Computational LinguisticsShuhe Wang, Xiaofei Sun, Xiaoya Li, et al.2025 · 436 citations
  86. AgentBench: Evaluating LLMs as AgentsarXiv:2308.03688Xiao Liu, Hao Yu, Hanchen Zhang, et al.2023 · 432 citations
  87. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  88. Large Language Models as OptimizersarXiv:2309.03409Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.2023 · 413 citations
  89. Automatic Prompt Optimization with “Gradient Descent” and Beam SearchConference on Empirical Methods in Natural Language Processing (EMNLP)Reid Pryzant, Dan Iter, Jerry Li, et al.2023 · 409 citations
  90. Do Prompt-Based Models Really Understand the Meaning of Their Prompts?Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Albert Webson, Ellie Pavlick2022 · 407 citations
  91. UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Tianbao Xie, Chen Henry Wu, Peng Shi, et al.2022 · 407 citations
  92. Enhancing Chat Language Models by Scaling High-quality Instructional ConversationsarXiv:2305.14233Ning Ding, Yulin Chen, Bokai Xu, et al.2023 · 402 citations
  93. Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
  94. DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-CorrectionConference on Neural Information Processing Systems (NeurIPS)Mohammadreza Pourreza, Davood Rafiei2023 · 401 citations
  95. LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhiqiang Hu, Lei Wang, Yihuai Lan, et al.2023 · 401 citations
  96. Llama Guard: LLM-based Input-Output Safeguard for Human-AI ConversationsarXiv:2312.06674Hakan Inan, Kartikeya Upasani, Jianfeng Chi, et al.2023 · 395 citations
  97. Large Language Models are Few-Shot Clinical Information ExtractorsConference on Empirical Methods in Natural Language Processing (EMNLP)Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.2022 · 384 citations
  98. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
  99. VILA: On Pre-training for Visual Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJi Lin, Hongxu Yin, Wei Ping, et al.2023 · 381 citations
  100. PaLI: A Jointly-Scaled Multilingual Language-Image ModelarXiv:2209.06794Xi Chen, Xiao Wang, Soravit Changpinyo, et al.2022 · 371 citations

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