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Who cites «The Power of Scale for Parameter-Efficient Prompt Tuning»

1,372 papers of our library cite it (of the 149,439 whose bibliographies we read) · 266 with a page here, the most cited first · page 1 of 3 · 1–100 · ← back to «The Power of Scale for Parameter-Efficient Prompt Tuning»

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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. LoRA: Low-Rank Adaptation of Large Language ModelsarXiv:2106.09685Edward J. Hu, Yelong Shen, Phillip Wallis, et al.2021 · 8,661 citations
  3. 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
  4. Efficient Memory Management for Large Language Model Serving with PagedAttentionarXiv:2309.06180Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, et al.2023 · 4,531 citations
  5. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  6. QLoRA: Efficient Finetuning of Quantized LLMsConference on Neural Information Processing Systems (NeurIPS)Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.2023 · 2,929 citations
  7. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  8. Flamingo: a Visual Language Model for Few-Shot LearningarXiv:2204.14198Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.2022 · 2,246 citations
  9. Finetuned Language Models Are Zero-Shot LearnersarXiv:2109.01652Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.2021 · 1,954 citations
  10. 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
  11. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
  12. Multitask Prompted Training Enables Zero-Shot Task GeneralizationarXiv:2110.08207Victor Sanh, Albert Webson, Colin Raffel, et al.2021 · 1,612 citations
  13. 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
  14. 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
  15. Program Synthesis with Large Language ModelsarXiv:2108.07732Jacob Austin, Augustus Odena, Maxwell Nye, et al.2021 · 1,192 citations
  16. 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
  17. Bias and Fairness in Large Language Models: A SurveyComputational LinguisticsIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,082 citations
  18. GPT Understands, TooAI OpenXiao Liu, Yanan Zheng, Zhengxiao Du, et al.2021 · 1,054 citations
  19. 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
  20. Universal and Transferable Adversarial Attacks on Aligned Language ModelsarXiv:2307.15043Andy Zou, Zifan Wang, Nicholas Carlini, et al.2023 · 1,005 citations
  21. PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 1,000 citations
  22. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 786 citations
  23. STaR: Bootstrapping Reasoning With ReasoningEric Zelikman, Yuhuai Wu, Jesse Mu, et al.2022 · 777 citations
  24. 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
  25. Large Language Models Are Human-Level Prompt EngineersarXiv:2211.01910Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.2022 · 701 citations
  26. 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
  27. Atlas: Few-shot Learning with Retrieval Augmented Language ModelsarXiv:2208.03299Gautier Izacard, Patrick Lewis, Maria Lomeli, et al.2022 · 673 citations
  28. Towards a Unified View of Parameter-Efficient Transfer LearningarXiv:2110.04366Junxian He, Chunting Zhou, Xuezhe Ma, et al.2021 · 619 citations
  29. 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
  30. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 607 citations
  31. 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
  32. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  33. 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
  34. 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
  35. 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
  36. Large Language Models as OptimizersarXiv:2309.03409Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.2023 · 413 citations
  37. 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
  38. 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
  39. 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
  40. Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
  41. 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
  42. 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
  43. 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
  44. 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
  45. Symbolic Knowledge Distillation: from General Language Models to Commonsense ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Peter West, Chandra Bhagavatula, Jack Hessel, et al.2022 · 349 citations
  46. UL2: Unifying Language Learning ParadigmsarXiv:2205.05131Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.2022 · 347 citations
  47. Large Language Models for Information Retrieval: A SurveyACM Transactions on Information SystemsYutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen2023 · 339 citations
  48. 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
  49. LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init AttentionarXiv:2303.16199Renrui Zhang, Jiaming Han, Chris Liu, et al.2023 · 333 citations
  50. 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
  51. AugGPT: Leveraging ChatGPT for Text Data AugmentationIEEE Transactions on Big DataHaixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li2023 · 306 citations
  52. SPoT: Better Frozen Model Adaptation through Soft Prompt TransferAnnual Meeting of the Association for Computational Linguistics (ACL)Tu Vu, Brian Lester, Noah Constant, et al.2022 · 306 citations
  53. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  54. An Explanation of In-context Learning as Implicit Bayesian InferencearXiv:2111.02080Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al.2021 · 286 citations
  55. OpenPrompt: An Open-source Framework for Prompt-learningAnnual Meeting of the Association for Computational Linguistics (ACL)Ning Ding, Shengding Hu, Weilin Zhao, et al.2022 · 279 citations
  56. Graph Retrieval-Augmented Generation: A SurveyACM Transactions on Information SystemsBoci Peng, Yun Zhu, Yongchao Liu, et al.2024 · 276 citations
  57. LongLoRA: Efficient Fine-tuning of Long-Context Large Language ModelsarXiv:2309.12307Yukang Chen, Shengju Qian, Haotian Tang, et al.2023 · 268 citations
  58. Multimodal Few-Shot Learning with Frozen Language ModelsarXiv:2106.13884Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, et al.2021 · 258 citations
  59. A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language ModelsarXiv:2401.01313S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, et al.2024 · 249 citations
  60. LaMP: When Large Language Models Meet PersonalizationAnnual Meeting of the Association for Computational Linguistics (ACL)Alireza Salemi, Sheshera Mysore, Michael Bendersky, et al.2024 · 246 citations
  61. OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of GeneralizationarXiv:2212.12017Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, et al.2022 · 244 citations
  62. Noisy Channel Language Model Prompting for Few-Shot Text ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Sewon Min, Mike Lewis, Hannaneh Hajishirzi, et al.2021 · 243 citations
  63. Reframing Instructional Prompts to GPTk's LanguageFindings of the Association for Computational LinguisticsSwaroop Mishra, Daniel Khashabi, Chitta Baral, et al.2022 · 242 citations
  64. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
  65. Visual Adversarial Examples Jailbreak Aligned Large Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceXiangyu Qi, Kaixuan Huang, Ashwinee Panda, et al.2023 · 240 citations
  66. G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question AnsweringConference on Neural Information Processing Systems (NeurIPS)Xiaoxin He, Yijun Tian, Yifei Sun, et al.2024 · 236 citations
  67. Steering Language Models With Activation EngineeringarXiv:2308.10248Alexander Matt Turner, Lisa Thiergart, Gavin Leech, et al.2023 · 233 citations
  68. LLaMA-Adapter V2: Parameter-Efficient Visual Instruction ModelarXiv:2304.15010Peng Gao, Jiaming Han, Renrui Zhang, et al.2023 · 229 citations
  69. 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
  70. 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
  71. Demystifying Prompts in Language Models via Perplexity EstimationarXiv:2212.04037Hila Gonen, Srini Iyer, Terra Blevins, et al.2022 · 213 citations
  72. Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 210 citations
  73. Active Example Selection for In-Context LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Yiming Zhang, Shi Feng, Chenhao Tan2022 · 209 citations
  74. Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2arXiv:2311.10702Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.2023 · 207 citations
  75. 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
  76. Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 202 citations
  77. SODA: Million-scale Dialogue Distillation with Social Commonsense ContextualizationConference on Empirical Methods in Natural Language Processing (EMNLP)Hyunwoo Kim, Jack Hessel, Liwei Jiang, et al.2023 · 202 citations
  78. 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
  79. 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
  80. Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt CollectionsarXiv:2104.04670Ruiqi Zhong, Kristy Lee, Zheng Zhang, et al.2021 · 195 citations
  81. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations
  82. GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Archiki Prasad, Peter Hase, Xiang Zhou, et al.2023 · 184 citations
  83. Adapting Language Models to Compress ContextsConference on Empirical Methods in Natural Language Processing (EMNLP)Alexis Chevalier, Alexander Wettig, Anirudh Ajith, et al.2023 · 182 citations
  84. Prompt-learning for Fine-grained Entity TypingFindings of the Association for Computational LinguisticsNing Ding, Yulin Chen, Xu Han, et al.2022 · 181 citations
  85. An Information-theoretic Approach to Prompt Engineering Without Ground Truth LabelsAnnual Meeting of the Association for Computational Linguistics (ACL)Taylor Sorensen, Joshua Robinson, Christopher Rytting, et al.2022 · 180 citations
  86. Learning to Compress Prompts with Gist TokensConference on Neural Information Processing Systems (NeurIPS)Jesse Mu, Xiang Lisa Li, Noah Goodman2023 · 178 citations
  87. Promptbreeder: Self-Referential Self-Improvement Via Prompt EvolutionarXiv:2309.16797Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al.2023 · 174 citations
  88. PromptSource: An Integrated Development Environment and Repository for Natural Language PromptsarXiv:2202.01279Stephen H. Bach, Victor Sanh, Zheng-Xin Yong, et al.2022 · 174 citations
  89. AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-TuningarXiv:2303.10512Qingru Zhang, Minshuo Chen, Alexander Bukharin, et al.2023 · 173 citations
  90. Quark: Controllable Text Generation with Reinforced UnlearningConference on Neural Information Processing Systems (NeurIPS)Ximing Lu, Sean Welleck, Jack Hessel, et al.2022 · 170 citations
  91. UniPELT: A Unified Framework for Parameter-Efficient Language Model TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Yuning Mao, Lambert Mathias, Rui Hou, et al.2022 · 165 citations
  92. Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceAntoine Louis, Gijs van Dijck, Gerasimos Spanakis2023 · 157 citations
  93. Fine-Tuning Language Models with Just Forward PassesConference on Neural Information Processing Systems (NeurIPS)Sadhika Malladi, Tianyu Gao, Eshaan Nichani, et al.2023 · 153 citations
  94. A Review on Language Models as Knowledge BasesarXiv:2204.06031Badr AlKhamissi, Millicent Li, Asli Celikyilmaz, et al.2022 · 150 citations
  95. ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool EmbeddingsConference on Neural Information Processing Systems (NeurIPS)Shibo Hao, Tianyang Liu, Zhen Wang, et al.2023 · 147 citations
  96. Is GPT-3 a Good Data Annotator?arXiv:2212.10450Bosheng Ding, Chengwei Qin, Linlin Liu, et al.2022 · 147 citations
  97. Efficient Methods for Natural Language Processing: A SurveyTransactions of the Association for Computational Linguistics (TACL)Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.2023 · 145 citations
  98. Dynamic Prefix-Tuning for Generative Template-based Event ExtractionAnnual Meeting of the Association for Computational Linguistics (ACL)Xiao Liu, Heyan Huang, Ge Shi, et al.2022 · 145 citations
  99. Iteratively Prompt Pre-trained Language Models for Chain of ThoughtConference on Empirical Methods in Natural Language Processing (EMNLP)Boshi Wang, Xiang Deng, Huan Sun2022 · 144 citations
  100. Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and DiscoveryConference on Neural Information Processing Systems (NeurIPS)Yuxin Wen, Neel Jain, John Kirchenbauer, et al.2023 · 141 citations

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