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Who cites Michele Catasta

3,880 citations of their works from 3,615 papers of our library (of the 149,439 whose bibliographies we read) · 1,001 with a page here, the most cited first · page 4 of 11 · 301–400 · ← Michele Catasta

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  1. MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUsarXiv:2402.15627Ziheng Jiang, Haibin Lin, Yinmin Zhong, et al.2024 · 157 citations
  2. Moshi: a speech-text foundation model for real-time dialoguearXiv:2410.00037Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.2024 · 157 citations
  3. Are aligned neural networks adversarially aligned?Conference on Neural Information Processing Systems (NeurIPS)Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, et al.2023 · 157 citations
  4. Lawyer LLaMA Technical ReportarXiv:2305.15062Quzhe Huang, Mingxu Tao, Chen Zhang, et al.2023 · 157 citations
  5. Locally Typical SamplingTransactions of the Association for Computational Linguistics (TACL)Clara Meister, Tiago Pimentel, Gian Wiher, et al.2023 · 157 citations
  6. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
  7. ROSCOE: A Suite of Metrics for Scoring Step-by-Step ReasoningarXiv:2212.07919Olga Golovneva, Moya Chen, Spencer Poff, et al.2022 · 155 citations
  8. Scientific Large Language Models: A Survey on Biological & Chemical DomainsACM Computing SurveysQiang Zhang, Keyang Ding, Tianwen Lyv, et al.2024 · 154 citations
  9. ART: Automatic multi-step reasoning and tool-use for large language modelsarXiv:2303.09014Bhargavi Paranjape, Scott Lundberg, Sameer Singh, et al.2023 · 154 citations
  10. LLM-based NLG Evaluation: Current Status and ChallengesComputational LinguisticsMingqi Gao, Xinyu Hu, Xunjian Yin, et al.2025 · 153 citations
  11. Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
  12. Generative Verifiers: Reward Modeling as Next-Token PredictionarXiv:2408.15240Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.2024 · 152 citations
  13. AnnoLLM: Making Large Language Models to Be Better Crowdsourced AnnotatorsarXiv:2303.16854Xingwei He, Zhenghao Lin, Yeyun Gong, et al.2023 · 152 citations
  14. Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and MitigationarXiv:2305.15852Niels Mundler, Jingxuan He, Slobodan Jenko, et al.2023 · 152 citations
  15. RA-DIT: Retrieval-Augmented Dual Instruction TuningarXiv:2310.01352Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.2023 · 149 citations
  16. MineDojo: Building Open-Ended Embodied Agents with Internet-Scale KnowledgearXiv:2206.08853Linxi Fan, Guanzhi Wang, Yunfan Jiang, et al.2022 · 149 citations
  17. TALM: Tool Augmented Language ModelsarXiv:2205.12255Aaron Parisi, Yao Zhao, Noah Fiedel2022 · 149 citations
  18. Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
  19. Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability CurvaturearXiv:2310.05130Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, et al.2023 · 148 citations
  20. Beyond Human Data: Scaling Self-Training for Problem-Solving with Language ModelsarXiv:2312.06585Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.2023 · 147 citations
  21. MLAgentBench: Evaluating Language Agents on Machine Learning ExperimentationarXiv:2310.03302Qian Huang, Jian Vora, Percy Liang, et al.2023 · 147 citations
  22. Is GPT-3 a Good Data Annotator?arXiv:2212.10450Bosheng Ding, Chengwei Qin, Linlin Liu, et al.2022 · 147 citations
  23. PMC-LLaMA: Towards Building Open-source Language Models for MedicinearXiv:2304.14454Chaoyi Wu, Weixiong Lin, Xiaoman Zhang, et al.2023 · 146 citations
  24. JudgeLM: Fine-tuned Large Language Models are Scalable JudgesarXiv:2310.17631Lianghui Zhu, Xinggang Wang, Xinlong Wang2023 · 145 citations
  25. MiniLLM: On-Policy Distillation of Large Language ModelsarXiv:2306.08543Yuxian Gu, Li Dong, Furu Wei, et al.2023 · 144 citations
  26. SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked PrefillsarXiv 2023Amey Agrawal, Ashish Panwar, Jayashree Mohan, et al.2023 · 144 citations
  27. Efficient Training of Language Models to Fill in the MiddlearXiv:2207.14255Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.2022 · 144 citations
  28. A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence GenerationarXiv:2307.03987Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu2023 · 143 citations
  29. Rethinking with Retrieval: Faithful Large Language Model InferencearXiv:2301.00303Hangfeng He, Hongming Zhang, Dan Roth2023 · 143 citations
  30. Understanding the Effects of RLHF on LLM Generalisation and DiversityarXiv:2310.06452Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.2023 · 143 citations
  31. PaliGemma: A versatile 3B VLM for transferarXiv:2407.07726Lucas Beyer, Andreas Steiner, Andre Susano Pinto, et al.2024 · 142 citations
  32. Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and FaithfulnessarXiv:2304.11633Bo Li, Gexiang Fang, Yang Yang, et al.2023 · 142 citations
  33. DeepInception: Hypnotize Large Language Model to Be JailbreakerarXiv:2311.03191Xuan Li, Zhanke Zhou, Jianing Zhu, et al.2023 · 141 citations
  34. SLiC-HF: Sequence Likelihood Calibration with Human FeedbackarXiv:2305.10425Yao Zhao, Rishabh Joshi, Tianqi Liu, et al.2023 · 141 citations
  35. CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding TasksarXiv:2105.12655Ruchir Puri, David S. Kung, Geert Janssen, et al.2021 · 141 citations
  36. Attributed Question Answering: Evaluation and Modeling for Attributed Large Language ModelsarXiv:2212.08037Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.2022 · 138 citations
  37. Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4VarXiv:2310.11441Jianwei Yang, Hao Zhang, Feng Li, et al.2023 · 137 citations
  38. A fine-grained comparison of pragmatic language understanding in humans and language modelsJennifer Hu, Sammy Floyd, Olessia Jouravlev, et al.2023 · 136 citations
  39. Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow InstructionsarXiv:2309.07875Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al.2023 · 135 citations
  40. Analyzing and Mitigating Object Hallucination in Large Vision-Language ModelsarXiv:2310.00754Yiyang Zhou, Chenhang Cui, Jaehong Yoon, et al.2023 · 134 citations
  41. FreshLLMs: Refreshing Large Language Models with Search Engine AugmentationarXiv:2310.03214Tu Vu, Mohit Iyyer, Xuezhi Wang, et al.2023 · 134 citations
  42. Simple synthetic data reduces sycophancy in large language modelsarXiv:2308.03958Jerry Wei, Da Huang, Yifeng Lu, et al.2023 · 134 citations
  43. The Impact of Positional Encoding on Length Generalization in TransformersConference on Neural Information Processing Systems (NeurIPS)Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, et al.2023 · 134 citations
  44. Improving Language Model Negotiation with Self-Play and In-Context Learning from AI FeedbackarXiv:2305.10142Yao Fu, Hao Peng, Tushar Khot, et al.2023 · 132 citations
  45. OpenWebMath: An Open Dataset of High-Quality Mathematical Web TextarXiv:2310.06786Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, et al.2023 · 132 citations
  46. Progressive-Hint Prompting Improves Reasoning in Large Language ModelsarXiv:2304.09797Chuanyang Zheng, Zhengying Liu, Enze Xie, et al.2023 · 131 citations
  47. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 129 citations
  48. Emergent autonomous scientific research capabilities of large language modelsarXiv:2304.05332 · published as "Autonomous chemical research with large language models", Nature (2023), doi:10.1038/s41586-023-06792-0Daniil A. Boiko, Robert MacKnight, Gabe Gomes2023 · 128 citations
  49. Time Travel in LLMs: Tracing Data Contamination in Large Language ModelsarXiv:2308.08493Shahriar Golchin, Mihai Surdeanu2023 · 128 citations
  50. LEVER: Learning to Verify Language-to-Code Generation with ExecutionarXiv:2302.08468Ansong Ni, Srini Iyer, Dragomir Radev, et al.2023 · 126 citations
  51. Take a Step Back: Evoking Reasoning via Abstraction in Large Language ModelsarXiv:2310.06117Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, et al.2023 · 126 citations
  52. PEER: A Collaborative Language ModelarXiv:2208.11663Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, et al.2022 · 126 citations
  53. Generative Judge for Evaluating AlignmentarXiv:2310.05470Junlong Li, Shichao Sun, Weizhe Yuan, et al.2023 · 125 citations
  54. A Systematic Evaluation of Large Language Models of CodearXiv:2202.13169Frank F. Xu, Uri Alon, Graham Neubig, et al.2022 · 125 citations
  55. H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language ModelsarXiv:2306.14048Zhenyu Zhang, Ying Sheng, Tianyi Zhou, et al.2023 · 124 citations
  56. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  57. Machine Learning for Ancient Languages: A SurveyComputational LinguisticsThea Sommerschield, Yannis Assael, John Pavlopoulos, et al.2023 · 124 citations
  58. Emergent and Predictable Memorization in Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, et al.2023 · 123 citations
  59. Finding Neurons in a Haystack: Case Studies with Sparse ProbingarXiv:2305.01610Wes Gurnee, Neel Nanda, Matthew Pauly, et al.2023 · 123 citations
  60. Large Language Models as Tool MakersarXiv:2305.17126Tianle Cai, Xuezhi Wang, Tengyu Ma, et al.2023 · 123 citations
  61. LongNet: Scaling Transformers to 1,000,000,000 TokensarXiv:2307.02486Jiayu Ding, Shuming Ma, Li Dong, et al.2023 · 123 citations
  62. CRUXEval: A Benchmark for Code Reasoning, Understanding and ExecutionarXiv:2401.03065Alex Gu, Baptiste Rozière, Hugh Leather, et al.2024 · 122 citations
  63. Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language ModelsarXiv:2408.00724Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.2024 · 122 citations
  64. RepoBench: Benchmarking Repository-Level Code Auto-Completion SystemsarXiv:2306.03091Tianyang Liu, Canwen Xu, Julian McAuley2023 · 122 citations

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