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Who cites «Finetuned Language Models Are Zero-Shot Learners»

1,887 papers of our library cite it (of the 149,439 whose bibliographies we read) · 499 with a page here, the most cited first · page 1 of 5 · 1–100 · ← back to «Finetuned Language Models Are Zero-Shot Learners»

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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. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  5. PaLM: Scaling Language Modeling with PathwaysarXiv:2204.02311Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.2022 · 4,753 citations
  6. 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
  7. Gemini: A Family of Highly Capable Multimodal ModelsarXiv:2312.11805Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.2023 · 3,050 citations
  8. QLoRA: Efficient Finetuning of Quantized LLMsConference on Neural Information Processing Systems (NeurIPS)Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.2023 · 2,929 citations
  9. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  10. 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
  11. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,269 citations
  12. Flamingo: a Visual Language Model for Few-Shot LearningarXiv:2204.14198Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.2022 · 2,246 citations
  13. TruthfulQA: Measuring How Models Mimic Human FalsehoodsAnnual Meeting of the Association for Computational Linguistics (ACL)Stephanie Lin, Jacob Hilton, Owain Evans2022 · 2,088 citations
  14. 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
  15. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
  16. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,669 citations
  17. Multitask Prompted Training Enables Zero-Shot Task GeneralizationarXiv:2110.08207Victor Sanh, Albert Webson, Colin Raffel, et al.2021 · 1,612 citations
  18. 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
  19. 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
  20. 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
  21. Code Llama: Open Foundation Models for CodearXiv:2308.12950Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.2024 · 1,430 citations
  22. 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
  23. 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
  24. InstructBLIP: Towards General-purpose Vision-Language Models with Instruction TuningarXiv:2305.06500Wenliang Dai, Junnan Li, Dongxu Li, et al.2023 · 1,100 citations
  25. 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
  26. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. 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
  33. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 786 citations
  34. STaR: Bootstrapping Reasoning With ReasoningEric Zelikman, Yuhuai Wu, Jesse Mu, et al.2022 · 777 citations
  35. 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
  36. 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
  37. 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
  38. 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
  39. Crosslingual Generalization through Multitask FinetuningarXiv:2211.01786Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.2022 · 703 citations
  40. Large Language Models Are Human-Level Prompt EngineersarXiv:2211.01910Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.2022 · 701 citations
  41. 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
  42. Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionarXiv:2310.11511Akari Asai, Zeqiu Wu, Yizhong Wang, et al.2023 · 677 citations
  43. Instruction Tuning with GPT-4arXiv:2304.03277Baolin Peng, Chunyuan Li, Pengcheng He, et al.2023 · 662 citations
  44. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 618 citations
  45. Instruction-Following Evaluation for Large Language ModelsarXiv:2311.07911Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.2023 · 615 citations
  46. 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
  47. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 607 citations
  48. ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIsarXiv:2307.16789Yujia Qin, Shihao Liang, Yining Ye, et al.2023 · 589 citations
  49. 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
  50. Galactica: A Large Language Model for SciencearXiv:2211.09085Ross Taylor, Marcin Kardas, Guillem Cucurull, et al.2022 · 570 citations
  51. 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
  52. Large Language Models Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
  53. 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
  54. 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
  55. 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
  56. GLaM: Efficient Scaling of Language Models with Mixture-of-ExpertsarXiv:2112.06905Nan Du, Yanping Huang, Andrew M. Dai, et al.2021 · 496 citations
  57. Orca: A Distributed Serving System for Transformer-Based Generative ModelsOSDI 2022Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, et al.2022 · 478 citations
  58. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
  59. 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
  60. 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
  61. 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
  62. 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
  63. 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
  64. AgentBench: Evaluating LLMs as AgentsarXiv:2308.03688Xiao Liu, Hao Yu, Hanchen Zhang, et al.2023 · 432 citations
  65. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  66. 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
  67. 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
  68. Enhancing Chat Language Models by Scaling High-quality Instructional ConversationsarXiv:2305.14233Ning Ding, Yulin Chen, Bokai Xu, et al.2023 · 402 citations
  69. Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
  70. 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
  71. Llama Guard: LLM-based Input-Output Safeguard for Human-AI ConversationsarXiv:2312.06674Hakan Inan, Kartikeya Upasani, Jianfeng Chi, et al.2023 · 395 citations
  72. 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
  73. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
  74. 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
  75. Augmented Language Models: a SurveyarXiv:2302.07842Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.2023 · 369 citations
  76. Orca: Progressive Learning from Complex Explanation Traces of GPT-4arXiv:2306.02707Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, et al.2023 · 369 citations
  77. A Survey on Large Language Models for Code GenerationACM Transactions on Software Engineering and MethodologyJuyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
  78. Unnatural Instructions: Tuning Language Models with (Almost) No Human LaborAnnual Meeting of the Association for Computational Linguistics (ACL)Or Honovich, Thomas Scialom, Omer Levy, et al.2023 · 366 citations
  79. Improving alignment of dialogue agents via targeted human judgementsarXiv:2209.14375Amelia Glaese, Nat McAleese, Maja Trębacz, et al.2022 · 362 citations
  80. ChatEval: Towards Better LLM-based Evaluators through Multi-Agent DebatearXiv:2308.07201Chi-Min Chan, Weize Chen, Yusheng Su, et al.2023 · 359 citations
  81. Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!arXiv:2310.03693Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.2023 · 355 citations
  82. Towards Mitigating LLM Hallucination via Self ReflectionFindings of the Association for Computational LinguisticsZiwei Ji, Tiezheng Yu, Yan Xu, et al.2023 · 354 citations
  83. Teaching Small Language Models to ReasonAnnual Meeting of the Association for Computational Linguistics (ACL)Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek, et al.2023 · 343 citations
  84. RLPrompt: Optimizing Discrete Text Prompts with Reinforcement LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.2022 · 338 citations
  85. LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init AttentionarXiv:2303.16199Renrui Zhang, Jiaming Han, Chris Liu, et al.2023 · 333 citations
  86. Discovering Language Model Behaviors with Model-Written EvaluationsarXiv:2212.09251Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.2022 · 328 citations
  87. MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
  88. How Far Can Camels Go? Exploring the State of Instruction Tuning on Open ResourcesConference on Neural Information Processing Systems (NeurIPS)Yizhong Wang, Hamish Ivison, Pradeep Dasigi, et al.2023 · 317 citations
  89. The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)arXiv:2309.17421Zhengyuan Yang, Linjie Li, Kevin Lin, et al.2023 · 311 citations
  90. Multi-step Jailbreaking Privacy Attacks on ChatGPTFindings of the Association for Computational LinguisticsHaoran Li, Dadi Guo, Wei Fan, et al.2023 · 304 citations
  91. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  92. Large Language Models are Effective Text Rankers with Pairwise Ranking PromptingFindings of the Association for Computational LinguisticsZhen Qin, Rolf Jagerman, Kai Hui, et al.2024 · 300 citations
  93. Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat DataConference on Empirical Methods in Natural Language Processing (EMNLP)Canwen Xu, Daya Guo, Nan Duan, et al.2023 · 296 citations
  94. MAmmoTH: Building Math Generalist Models through Hybrid Instruction TuningarXiv:2309.05653Xiang Yue, Xingwei Qu, Ge Zhang, et al.2023 · 295 citations
  95. Can language models learn from explanations in context?Findings of the Association for Computational LinguisticsAndrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.2022 · 295 citations
  96. Prompting Large Language Model for Machine Translation: A Case StudyarXiv:2301.07069Biao Zhang, Barry Haddow, Alexandra Birch2023 · 294 citations
  97. Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
  98. Llemma: An Open Language Model For MathematicsarXiv:2310.10631Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.2023 · 286 citations
  99. An Explanation of In-context Learning as Implicit Bayesian InferencearXiv:2111.02080Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al.2021 · 286 citations
  100. Larger language models do in-context learning differentlyarXiv:2303.03846Jerry Wei, Jason Wei, Yi Tay, et al.2023 · 285 citations

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