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Who cites Joshua Maynez

6,699 citations of their works from 5,987 papers of our library (of the 149,439 whose bibliographies we read) · 1,482 with a page here, the most cited first · page 3 of 15 · 201–300 · ← Joshua Maynez

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  1. Text Classification via Large Language ModelsFindings of the Association for Computational LinguisticsXiaofei Sun, Xiaoya Li, Jiwei Li, et al.2023 · 292 citations
  2. QAFactEval: Improved QA-Based Factual Consistency Evaluation for SummarizationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, et al.2022 · 292 citations
  3. A Review of Large Language Models and Autonomous Agents in ChemistryarXiv:2407.01603Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White2024 · 288 citations
  4. 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
  5. Llemma: An Open Language Model For MathematicsarXiv:2310.10631Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.2023 · 286 citations
  6. DSPy: Compiling Declarative Language Model Calls into Self-Improving PipelinesarXiv:2310.03714Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.2023 · 285 citations
  7. Larger language models do in-context learning differentlyarXiv:2303.03846Jerry Wei, Jason Wei, Yi Tay, et al.2023 · 285 citations
  8. MEGA: Multilingual Evaluation of Generative AIarXiv:2303.12528Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.2023 · 285 citations
  9. AlignScore: Evaluating Factual Consistency with A Unified Alignment FunctionAnnual Meeting of the Association for Computational Linguistics (ACL)Yuheng Zha, Yichi Yang, Ruichen Li, et al.2023 · 284 citations
  10. 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
  11. Generate rather than Retrieve: Large Language Models are Strong Context GeneratorsarXiv:2209.10063Wenhao Yu, Dan Iter, Shuohang Wang, et al.2022 · 281 citations
  12. Large Language Models for Mathematical Reasoning: Progresses and ChallengesConference of the European Chapter of the Association for Computational Linguistics (EACL)Janice Ahn, Rishu Verma, Renze Lou, et al.2024 · 280 citations
  13. An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language ModelsLecture notes in computer scienceLiang Chen, Haozhe Zhao, Tianyu Liu, et al.2024 · 279 citations
  14. TRUE: Re-evaluating Factual Consistency EvaluationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Or Honovich, Roee Aharoni, Jonathan Herzig, et al.2022 · 279 citations
  15. A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future DirectionsComputational LinguisticsJunchao Wu, Shu Yang, Runzhe Zhan, et al.2025 · 277 citations
  16. Are We on the Right Way for Evaluating Large Vision-Language Models?Conference on Neural Information Processing Systems (NeurIPS)Lin Chen, Jinsong Li, Xiaoyi Dong, et al.2024 · 277 citations
  17. LLM-QAT: Data-Free Quantization Aware Training for Large Language ModelsFindings of the Association for Computational LinguisticsZechun Liu, Barlas Oguz, Changsheng Zhao, et al.2024 · 276 citations
  18. Corrective Retrieval Augmented GenerationarXiv:2401.15884Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, et al.2024 · 273 citations
  19. GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language ModelsarXiv:2410.05229Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.2024 · 273 citations
  20. Reducing Activation Recomputation in Large Transformer ModelsarXiv:2205.05198Vijay Korthikanti, Jared Casper, Sangkug Lym, et al.2022 · 273 citations
  21. Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What MattersAnnual Meeting of the Association for Computational Linguistics (ACL)Boshi Wang, Sewon Min, Xiang Deng, et al.2023 · 272 citations
  22. MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
  23. 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
  24. OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer EnvironmentsConference on Neural Information Processing Systems (NeurIPS)Tianbao Xie, Danyang Zhang, Jixuan Chen, et al.2024 · 264 citations
  25. The Effect of Sampling Temperature on Problem Solving in Large Language ModelsFindings of the Association for Computational LinguisticsMatthew Renze2024 · 263 citations
  26. Large Language Models for Data Annotation and Synthesis: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Tan, Dawei Li, Song Wang, et al.2024 · 262 citations
  27. Large Language Models Sensitivity to The Order of Options in Multiple-Choice QuestionsFindings of the Association for Computational LinguisticsPouya Pezeshkpour, Estevam Hruschka2023 · 261 citations
  28. Scaling Relationship on Learning Mathematical Reasoning with Large Language ModelsarXiv:2308.01825Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.2023 · 261 citations
  29. RedPajama: an Open Dataset for Training Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Maurice Weber, Daniel Fu, Quentin Anthony, et al.2024 · 260 citations
  30. CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive SummarizationConference on Empirical Methods in Natural Language Processing (EMNLP)Shuyang Cao, Lu Wang2021 · 260 citations
  31. Contrastive Decoding: Open-ended Text Generation as OptimizationarXiv:2210.15097Xiang Lisa Li, Ari Holtzman, Daniel Fried, et al.2022 · 254 citations
  32. Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 253 citations
  33. InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingLecture notes in computer scienceYi Wang, Kunchang Li, Xinhao Li, et al.2024 · 253 citations
  34. GPT-RE: In-context Learning for Relation Extraction using Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al.2023 · 253 citations
  35. Personality Traits in Large Language ModelsarXiv:2307.00184Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al.2023 · 252 citations
  36. RAFT: Reward rAnked FineTuning for Generative Foundation Model AlignmentarXiv:2304.06767Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.2023 · 252 citations
  37. Trusting Your Evidence: Hallucinate Less with Context-aware DecodingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Weijia Shi, Xiaochuang Han, Mike Lewis, et al.2024 · 249 citations
  38. Language Models can Solve Computer TasksConference on Neural Information Processing Systems (NeurIPS)Geunwoo Kim, Pierre Baldi, Stephen McAleer2023 · 249 citations
  39. Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and ToxicityarXiv:2301.12867Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.2023 · 249 citations
  40. Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts ArchitecturearXiv:2306.16092Jiaxi Cui; Munan Ning; Zongjian Li; Bohua Chen; Yang Yan; Hao Li; Bin Ling; Yonghong Tian;, Li Yuan2023 · 248 citations
  41. MedAgents: Large Language Models as Collaborators for Zero-shot Medical ReasoningFindings of the Association for Computational LinguisticsXiangru Tang, Anni Zou, Zhuosheng Zhang, et al.2024 · 246 citations
  42. Hallucinations in Large Multilingual Translation ModelsTransactions of the Association for Computational Linguistics (TACL)Nuno M. Guerreiro, Duarte M. Alves, Jonas Waldendorf, et al.2023 · 244 citations
  43. Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-ThoughtarXiv:2210.01240Abulhair Saparov, He He2022 · 244 citations
  44. 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
  45. LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation DatasetarXiv:2309.11998Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.2023 · 242 citations
  46. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
  47. Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video UnderstandingarXiv:2306.02858Hang Zhang, Xin Li, Lidong Bing2023 · 238 citations
  48. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
  49. Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human SupervisionConference on Neural Information Processing Systems (NeurIPS)Zhiqing Sun, Yikang Shen, Qinhong Zhou, et al.2023 · 236 citations
  50. What learning algorithm is in-context learning? Investigations with linear modelsarXiv:2211.15661Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.2022 · 236 citations
  51. Evaluating Open-Domain Question Answering in the Era of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Ehsan Kamalloo, Nouha Dziri, Charles Clarke, et al.2023 · 233 citations
  52. MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?Lecture notes in computer scienceRenrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.2024 · 232 citations
  53. GAIA: a benchmark for General AI AssistantsarXiv:2311.12983Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.2023 · 232 citations
  54. Detecting Hallucinated Content in Conditional Neural Sequence GenerationFindings of the Association for Computational LinguisticsChunting Zhou, Graham Neubig, Jiatao Gu, et al.2021 · 232 citations
  55. Beyond neural scaling laws: beating power law scaling via data pruningConference on Neural Information Processing Systems (NeurIPS)Ben Sorscher, Robert Geirhos, Shashank Shekhar, et al.2022 · 231 citations
  56. Self-critiquing models for assisting human evaluatorsarXiv:2206.05802William Saunders, Catherine Yeh, Jeff Wu, et al.2022 · 228 citations
  57. 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
  58. How Language Model Hallucinations Can SnowballarXiv:2305.13534Muru Zhang, Ofir Press, William Merrill, et al.2023 · 226 citations
  59. ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem SolvingarXiv:2309.17452Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 225 citations
  60. 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
  61. Specializing Smaller Language Models towards Multi-Step ReasoningarXiv:2301.12726Yao Fu, Hao Peng, Litu Ou, et al.2023 · 224 citations
  62. GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical InformationBioinformaticsQiao Jin, Yifan Yang, Qingyu Chen, et al.2023 · 223 citations
  63. NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding ModelsarXiv:2405.17428Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.2024 · 222 citations
  64. Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLParXiv:2212.14024Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.2022 · 222 citations
  65. PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about ChangeConference on Neural Information Processing Systems (NeurIPS)Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.2022 · 222 citations
  66. A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource LanguagesAnnual Meeting of the Association for Computational Linguistics (ACL)Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot2020 · 222 citations
  67. OpenHands: An Open Platform for AI Software Developers as Generalist AgentsarXiv:2407.16741Xingyao Wang, Boxuan Li, Yufan Song, et al.2024 · 221 citations
  68. AlpaGasus: Training A Better Alpaca with Fewer DataarXiv:2307.08701Lichang Chen, Shiyang Li, Jun Yan, et al.2023 · 220 citations
  69. Distilling Reasoning Capabilities into Smaller Language ModelsFindings of the Association for Computational LinguisticsKumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan2023 · 219 citations
  70. FOLIO: Natural Language Reasoning with First-Order LogicarXiv:2209.00840Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.2022 · 219 citations
  71. Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language ModelsarXiv:2308.16149Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.2023 · 218 citations
  72. Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mosh Levy, Alon Jacoby, Yoav Goldberg2024 · 217 citations
  73. AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent BehaviorsarXiv:2308.10848Weize Chen, Yusheng Su, Jingwei Zuo, et al.2023 · 217 citations
  74. Making Language Models Better Reasoners with Step-Aware VerifierAnnual Meeting of the Association for Computational Linguistics (ACL)Yifei Li, Zeqi Lin, Shizhuo Zhang, et al.2023 · 217 citations
  75. Safe RLHF: Safe Reinforcement Learning from Human FeedbackarXiv:2310.12773Josef Dai, Xuehai Pan, Ruiyang Sun, et al.2023 · 217 citations
  76. InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal ModelsarXiv:2504.10479Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.2025 · 216 citations
  77. LLM+P: Empowering Large Language Models with Optimal Planning ProficiencyarXiv:2304.11477Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.2023 · 216 citations
  78. Annotating and Modeling Fine-grained Factuality in SummarizationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Tanya Goyal, Greg Durrett2021 · 216 citations
  79. LLM2Vec: Large Language Models Are Secretly Powerful Text EncodersarXiv:2404.05961Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, et al.2024 · 213 citations
  80. MADLAD-400: A Multilingual And Document-Level Large Audited DatasetConference on Neural Information Processing Systems (NeurIPS)Sneha Kudugunta, Isaac Caswell, Biao Zhang, et al.2023 · 213 citations
  81. 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
  82. 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
  83. Sources of Hallucination by Large Language Models on Inference TasksFindings of the Association for Computational LinguisticsNick McKenna, Tianyi Li, Liang Cheng, et al.2023 · 212 citations
  84. Language Models of Code are Few-Shot Commonsense LearnersConference on Empirical Methods in Natural Language Processing (EMNLP)Aman Madaan, Shuyan Zhou, Uri Alon, et al.2022 · 212 citations
  85. ChemCrow: Augmenting large-language models with chemistry toolsarXiv:2304.05376Andres M Bran, Sam Cox, Oliver Schilter, et al.2023 · 211 citations
  86. “Kelly is a Warm Person, Joseph is a Role Model”: Gender Biases in LLM-Generated Reference LettersFindings of the Association for Computational LinguisticsYixin Wan, George Pu, Jiao Sun, et al.2023 · 211 citations
  87. From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder PipelinearXiv:2406.11939Tianle Li, Wei-Lin Chiang, Evan Frick, et al.2024 · 210 citations
  88. Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 210 citations
  89. SALMONN: Towards Generic Hearing Abilities for Large Language ModelsarXiv:2310.13289Changli Tang, Wenyi Yu, Guangzhi Sun, et al.2023 · 209 citations
  90. 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
  91. DeepSeek-VL: Towards Real-World Vision-Language UnderstandingarXiv:2403.05525Haoyu Lu, Wen Liu, Bo Zhang, et al.2024 · 208 citations
  92. Exploring Human-Like Translation Strategy with Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Zhiwei He, Tian Liang, Wenxiang Jiao, et al.2024 · 207 citations
  93. Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2arXiv:2311.10702Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.2023 · 207 citations
  94. BLINK: Multimodal Large Language Models Can See but Not PerceiveLecture notes in computer scienceXingyu Fu, Yushi Hu, Bangzheng Li, et al.2024 · 206 citations
  95. Evaluating Factuality in Generation with Dependency-level EntailmentFindings of the Association for Computational LinguisticsTanya Goyal, Greg Durrett2020 · 205 citations
  96. Autoformalization with Large Language ModelsarXiv:2205.12615Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.2022 · 204 citations
  97. Measuring Multimodal Mathematical Reasoning with MATH-Vision DatasetConference on Neural Information Processing Systems (NeurIPS)Ke Wang, Junting Pan, Weikang Shi, et al.2024 · 203 citations
  98. DAGA: Data Augmentation with a Generation Approach for Low-resource Tagging TasksConference on Empirical Methods in Natural Language Processing (EMNLP)Bosheng Ding, Linlin Liu, Lidong Bing, et al.2020 · 203 citations
  99. RRHF: Rank Responses to Align Language Models with Human Feedback without tearsarXiv:2304.05302Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 201 citations
  100. ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree SearchConference on Neural Information Processing Systems (NeurIPS)Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.2024 · 200 citations

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