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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 2 of 8 · 101–200 · ← Brian Lester

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  1. Augmented Language Models: a SurveyarXiv:2302.07842Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.2023 · 369 citations
  2. Orca: Progressive Learning from Complex Explanation Traces of GPT-4arXiv:2306.02707Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, et al.2023 · 369 citations
  3. 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
  4. 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
  5. Improving alignment of dialogue agents via targeted human judgementsarXiv:2209.14375Amelia Glaese, Nat McAleese, Maja Trębacz, et al.2022 · 362 citations
  6. ChatEval: Towards Better LLM-based Evaluators through Multi-Agent DebatearXiv:2308.07201Chi-Min Chan, Weize Chen, Yusheng Su, et al.2023 · 359 citations
  7. 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
  8. Towards Mitigating LLM Hallucination via Self ReflectionFindings of the Association for Computational LinguisticsZiwei Ji, Tiezheng Yu, Yan Xu, et al.2023 · 354 citations
  9. 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
  10. UL2: Unifying Language Learning ParadigmsarXiv:2205.05131Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.2022 · 347 citations
  11. 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
  12. 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
  13. 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
  14. LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init AttentionarXiv:2303.16199Renrui Zhang, Jiaming Han, Chris Liu, et al.2023 · 333 citations
  15. Discovering Language Model Behaviors with Model-Written EvaluationsarXiv:2212.09251Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.2022 · 328 citations
  16. 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
  17. 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
  18. The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)arXiv:2309.17421Zhengyuan Yang, Linjie Li, Kevin Lin, et al.2023 · 311 citations
  19. Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defenseConference on Neural Information Processing Systems (NeurIPS)Kalpesh Krishna, Yixiao Song, Marzena Karpinska, et al.2023 · 310 citations
  20. 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
  21. 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
  22. Multi-step Jailbreaking Privacy Attacks on ChatGPTFindings of the Association for Computational LinguisticsHaoran Li, Dadi Guo, Wei Fan, et al.2023 · 304 citations
  23. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  24. 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
  25. 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
  26. MAmmoTH: Building Math Generalist Models through Hybrid Instruction TuningarXiv:2309.05653Xiang Yue, Xingwei Qu, Ge Zhang, et al.2023 · 295 citations
  27. 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
  28. Prompting Large Language Model for Machine Translation: A Case StudyarXiv:2301.07069Biao Zhang, Barry Haddow, Alexandra Birch2023 · 294 citations
  29. 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
  30. Llemma: An Open Language Model For MathematicsarXiv:2310.10631Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.2023 · 286 citations
  31. An Explanation of In-context Learning as Implicit Bayesian InferencearXiv:2111.02080Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al.2021 · 286 citations
  32. Larger language models do in-context learning differentlyarXiv:2303.03846Jerry Wei, Jason Wei, Yi Tay, et al.2023 · 285 citations
  33. MEGA: Multilingual Evaluation of Generative AIarXiv:2303.12528Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.2023 · 285 citations
  34. A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series ModelsarXiv:2303.10420Junjie Ye, Xuanting Chen, Nuo Xu, et al.2023 · 283 citations
  35. Generate rather than Retrieve: Large Language Models are Strong Context GeneratorsarXiv:2209.10063Wenhao Yu, Dan Iter, Shuohang Wang, et al.2022 · 281 citations
  36. 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
  37. Surface Form Competition: Why the Highest Probability Answer Isn't Always RightConference on Empirical Methods in Natural Language Processing (EMNLP)Ari Holtzman, Peter West, Vered Shwartz, et al.2021 · 277 citations
  38. Graph Retrieval-Augmented Generation: A SurveyACM Transactions on Information SystemsBoci Peng, Yun Zhu, Yongchao Liu, et al.2024 · 276 citations
  39. MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
  40. Large Language Models Are Zero-Shot Time Series ForecastersConference on Neural Information Processing Systems (NeurIPS)Nate Gruver, Marc Finzi, Shikai Qiu, et al.2023 · 268 citations
  41. LongLoRA: Efficient Fine-tuning of Long-Context Large Language ModelsarXiv:2309.12307Yukang Chen, Shengju Qian, Haotian Tang, et al.2023 · 268 citations
  42. Predictability and Surprise in Large Generative ModelsACM Conference on Fairness, Accountability, and Transparency (FAccT)Deep Ganguli, Danny Hernandez, Liane Lovitt, et al.2022 · 268 citations
  43. A General Theoretical Paradigm to Understand Learning from Human PreferencesarXiv:2310.12036Mohammad Gheshlaghi Azar, Mark Rowland, Bilal Piot, et al.2023 · 263 citations
  44. LLaMA-VID: An Image is Worth 2 Tokens in Large Language ModelsLecture notes in computer scienceYanwei Li, Chengyao Wang, Jiaya Jia2023 · 262 citations
  45. Scaling Relationship on Learning Mathematical Reasoning with Large Language ModelsarXiv:2308.01825Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.2023 · 261 citations
  46. DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT ModelsConference on Neural Information Processing Systems (NeurIPS)Boxin Wang, Weixin Chen, Hengzhi Pei, et al.2023 · 259 citations
  47. Multimodal Few-Shot Learning with Frozen Language ModelsarXiv:2106.13884Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, et al.2021 · 258 citations
  48. Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 253 citations
  49. Personality Traits in Large Language ModelsarXiv:2307.00184Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al.2023 · 252 citations
  50. RAFT: Reward rAnked FineTuning for Generative Foundation Model AlignmentarXiv:2304.06767Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.2023 · 252 citations
  51. NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each BenchmarkFindings of the Association for Computational LinguisticsOscar Sainz, Jon Campos, Iker García-Ferrero, et al.2023 · 250 citations
  52. 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
  53. Language Models can Solve Computer TasksConference on Neural Information Processing Systems (NeurIPS)Geunwoo Kim, Pierre Baldi, Stephen McAleer2023 · 249 citations
  54. 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
  55. ZeroGen: Efficient Zero-shot Learning via Dataset GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Jiacheng Ye, Jiahui Gao, Qintong Li, et al.2022 · 245 citations
  56. 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
  57. 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
  58. Synthetic Data Generation with Large Language Models for Text Classification: Potential and LimitationsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, et al.2023 · 242 citations
  59. Reframing Instructional Prompts to GPTk's LanguageFindings of the Association for Computational LinguisticsSwaroop Mishra, Daniel Khashabi, Chitta Baral, et al.2022 · 242 citations
  60. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
  61. 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
  62. Translation between Molecules and Natural LanguageConference on Empirical Methods in Natural Language Processing (EMNLP)Carl Edwards, Tuan Lai, Kevin Ros, et al.2022 · 238 citations
  63. 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
  64. Detecting and Preventing Hallucinations in Large Vision Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceAnisha Gunjal, Jihan Yin, Erhan Bas2023 · 235 citations
  65. Steering Language Models With Activation EngineeringarXiv:2308.10248Alexander Matt Turner, Lisa Thiergart, Gavin Leech, et al.2023 · 233 citations
  66. LLaMA-Adapter V2: Parameter-Efficient Visual Instruction ModelarXiv:2304.15010Peng Gao, Jiaming Han, Renrui Zhang, et al.2023 · 229 citations
  67. Tower: An Open Multilingual Large Language Model for Translation-Related TasksarXiv:2402.17733Duarte M. Alves, Jose Pombal, Nuno M. Guerreiro, et al.2024 · 227 citations
  68. How Language Model Hallucinations Can SnowballarXiv:2305.13534Muru Zhang, Ofir Press, William Merrill, et al.2023 · 226 citations
  69. 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
  70. NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding ModelsarXiv:2405.17428Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.2024 · 222 citations
  71. 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
  72. AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent BehaviorsarXiv:2308.10848Weize Chen, Yusheng Su, Jingwei Zuo, et al.2023 · 217 citations
  73. 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
  74. LLM+P: Empowering Large Language Models with Optimal Planning ProficiencyarXiv:2304.11477Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.2023 · 216 citations
  75. 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
  76. Demystifying Prompts in Language Models via Perplexity EstimationarXiv:2212.04037Hila Gonen, Srini Iyer, Terra Blevins, et al.2022 · 213 citations
  77. 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
  78. 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
  79. Generating Training Data with Language Models: Towards Zero-Shot Language UnderstandingarXiv:2202.04538Yu Meng, Jiaxin Huang, Yu Zhang, et al.2022 · 210 citations
  80. Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 210 citations
  81. 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
  82. SALMONN: Towards Generic Hearing Abilities for Large Language ModelsarXiv:2310.13289Changli Tang, Wenyi Yu, Guangzhi Sun, et al.2023 · 209 citations
  83. Active Example Selection for In-Context LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Yiming Zhang, Shi Feng, Chenhao Tan2022 · 209 citations
  84. 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
  85. 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
  86. Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2arXiv:2311.10702Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.2023 · 207 citations
  87. 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
  88. Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 202 citations
  89. 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
  90. 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
  91. 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
  92. 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
  93. Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human FeedbackConference on Empirical Methods in Natural Language Processing (EMNLP)Viet Lai, Chien Nguyen, Nghia Ngo, et al.2023 · 195 citations
  94. 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
  95. One Embedder, Any Task: Instruction-Finetuned Text EmbeddingsarXiv:2212.09741Hongjin Su, Weijia Shi, Jungo Kasai, et al.2022 · 193 citations
  96. Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMsarXiv:2412.21187Xingyu Chen, Jiahao Xu, Tian Liang, et al.2024 · 192 citations
  97. On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Omar Shaikh, Hongxin Zhang, William Held, et al.2023 · 192 citations
  98. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
  99. Towards Making the Most of ChatGPT for Machine TranslationFindings of the Association for Computational LinguisticsKeqin Peng, Liang Ding, Qihuang Zhong, et al.2023 · 190 citations
  100. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations

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