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Who cites USVSN Sai Prashanth

521 citations of their works from 506 papers of our library (of the 149,439 whose bibliographies we read) · 136 with a page here, the most cited first · page 1 of 2 · 1–100 · ← USVSN Sai Prashanth

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  1. LLaMA: Open and Efficient Foundation Language ModelsarXiv:2302.13971Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al.2023 · 9,603 citations
  2. A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,231 citations
  3. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  4. 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
  5. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
  6. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,669 citations
  7. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextarXiv:2403.05530Gemini Team, Petko Georgiev, Ving Ian Lei, et al.2024 · 1,589 citations
  8. Code Llama: Open Foundation Models for CodearXiv:2308.12950Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.2024 · 1,430 citations
  9. 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
  10. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 786 citations
  11. Crosslingual Generalization through Multitask FinetuningarXiv:2211.01786Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.2022 · 703 citations
  12. 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
  13. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 618 citations
  14. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  15. DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability CurvaturearXiv:2301.11305Eric Mitchell, Yoonho Lee, Alexander Khazatsky, et al.2023 · 481 citations
  16. CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-XACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)Qinkai Zheng, Xiao Xia, Xu Zou, et al.2023 · 465 citations
  17. The Falcon Series of Open Language ModelsarXiv:2311.16867Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.2023 · 443 citations
  18. BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical DomainsFindings of the Association for Computational LinguisticsYanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.2024 · 409 citations
  19. 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
  20. Large Language Models Struggle to Learn Long-Tail KnowledgearXiv:2211.08411Nikhil Kandpal, Haikang Deng, Adam Roberts, et al.2022 · 366 citations
  21. Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and InferencearXiv:2412.13663Benjamin Warner, Antoine Chaffin, Benjamin Clavié, et al.2024 · 358 citations
  22. PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial PromptsarXiv:2306.04528Kaijie Zhu, Jindong Wang, Jiaheng Zhou, et al.2023 · 305 citations
  23. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  24. Llemma: An Open Language Model For MathematicsarXiv:2310.10631Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.2023 · 286 citations
  25. 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
  26. 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
  27. 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
  28. Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video UnderstandingarXiv:2306.02858Hang Zhang, Xin Li, Lidong Bing2023 · 238 citations
  29. 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
  30. FOLIO: Natural Language Reasoning with First-Order LogicarXiv:2209.00840Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.2022 · 219 citations
  31. Why Does Surprisal From Larger Transformer-Based Language Models Provide a Poorer Fit to Human Reading Times?Transactions of the Association for Computational Linguistics (TACL)Byung-Doh Oh, William Schuler2023 · 211 citations
  32. What Can Transformers Learn In-Context? A Case Study of Simple Function ClassesConference on Neural Information Processing Systems (NeurIPS)Shivam Garg, Dimitris Tsipras, Percy Liang, et al.2022 · 209 citations
  33. mGPT: Few-Shot Learners Go MultilingualarXiv:2204.07580Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, et al.2022 · 203 citations
  34. 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
  35. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and ValidationArtificial Intelligence ReviewXiaowei Huang, Wenjie Ruan, Wei Huang, et al.2023 · 199 citations
  36. 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
  37. Eliciting Latent Predictions from Transformers with the Tuned LensarXiv:2303.08112Nora Belrose, Igor Ostrovsky, Lev McKinney, et al.2023 · 188 citations
  38. Deja Vu: Contextual Sparsity for Efficient LLMs at Inference TimeInternational Conference on Machine Learning (ICML)Zichang Liu, Jue Wang, Tri Dao, et al.2023 · 185 citations
  39. 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
  40. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  41. On the Robustness of ChatGPT: An Adversarial and Out-of-distribution PerspectivearXiv:2302.12095Jindong Wang, Xixu Hu, Wenxin Hou, et al.2023 · 176 citations
  42. Baldur: Whole-Proof Generation and Repair with Large Language ModelsarXiv:2303.04910Emily First, Markus N. Rabe, Talia Ringer, et al.2023 · 175 citations
  43. Do All Languages Cost the Same? Tokenization in the Era of Commercial Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.2023 · 174 citations
  44. DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated TextFindings of the Association for Computational LinguisticsJinyan Su, Terry Zhuo, Di Wang, et al.2023 · 172 citations
  45. Evaluating and Inducing Personality in Pre-trained Language ModelsConference on Neural Information Processing Systems (NeurIPS)Guangyuan Jiang, Manjie Xu, Song-Chun Zhu, et al.2022 · 168 citations
  46. The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Junyi Li, Jie Chen, Ruiyang Ren, et al.2024 · 153 citations
  47. The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual DatasetarXiv:2303.03915Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.2023 · 150 citations
  48. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
  49. 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
  50. Is GPT-3 a Good Data Annotator?arXiv:2212.10450Bosheng Ding, Chengwei Qin, Linlin Liu, et al.2022 · 147 citations
  51. SCOTT: Self-Consistent Chain-of-Thought DistillationAnnual Meeting of the Association for Computational Linguistics (ACL)Peifeng Wang, Zhengyang Wang, Zheng Li, et al.2023 · 146 citations
  52. Investigating Data Contamination in Modern Benchmarks for Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.2024 · 137 citations
  53. PMET: Precise Model Editing in a TransformerProceedings of the AAAI Conference on Artificial IntelligenceXiaopeng Li; Shasha Li; Shezheng Song; Jing Yang; Jun Ma;, Jie Yu2023 · 135 citations
  54. You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual SettingsBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsZeerak Talat, Aurélie Névéol, Stella Biderman, et al.2022 · 130 citations
  55. MAGE: Machine-generated Text Detection in the WildAnnual Meeting of the Association for Computational Linguistics (ACL)Yafu Li, Qintong Li, Leyang Cui, et al.2024 · 129 citations
  56. OpenCodeInterpreter: Integrating Code Generation with Execution and RefinementFindings of the Association for Computational LinguisticsTianyu Zheng, Ge Zhang, Tianhao Shen, et al.2024 · 129 citations
  57. Function Vectors in Large Language ModelsarXiv:2310.15213Eric Todd, Millicent L. Li, Arnab Sen Sharma, et al.2023 · 127 citations
  58. A Systematic Evaluation of Large Language Models of CodearXiv:2202.13169Frank F. Xu, Uri Alon, Graham Neubig, et al.2022 · 125 citations
  59. H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language ModelsarXiv:2306.14048Zhenyu Zhang, Ying Sheng, Tianyi Zhou, et al.2023 · 124 citations
  60. 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
  61. The case for 4-bit precision: k-bit Inference Scaling LawsarXiv:2212.09720Tim Dettmers, Luke Zettlemoyer2022 · 123 citations
  62. Physics of Language Models: Part 3.1, Knowledge Storage and ExtractionarXiv:2309.14316Zeyuan Allen-Zhu, Yuanzhi Li2023 · 116 citations
  63. DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming HeadsarXiv:2410.10819Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al.2024 · 114 citations
  64. GoLLIE: Annotation Guidelines improve Zero-Shot Information-ExtractionarXiv:2310.03668Oscar Sainz, Iker Garcia-Ferrero, Rodrigo Agerri, et al.2023 · 114 citations
  65. Ground-Truth Labels Matter: A Deeper Look into Input-Label DemonstrationsConference on Empirical Methods in Natural Language Processing (EMNLP)Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.2022 · 114 citations
  66. Efficient Large Language Models: A SurveyarXiv:2312.03863Zhongwei Wan, Xin Wang, Che Liu, et al.2023 · 110 citations
  67. A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & ToxicityarXiv:2305.13169Shayne Longpre, Gregory Yauney, Emily Reif, et al.2023 · 104 citations
  68. BLOOM+1: Adding Language Support to BLOOM for Zero-Shot PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, et al.2023 · 102 citations
  69. A Careful Examination of Large Language Model Performance on Grade School ArithmeticConference on Neural Information Processing Systems (NeurIPS)Hugh Zhang, Jeff Da, Dean Lee, et al.2024 · 101 citations
  70. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 96 citations
  71. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
  72. How well do Large Language Models perform in Arithmetic tasks?arXiv:2304.02015Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 93 citations
  73. On the Tool Manipulation Capability of Open-source Large Language ModelsarXiv:2305.16504Qiantong Xu, Fenglu Hong, Bo Li, et al.2023 · 92 citations
  74. What's In My Big Data?arXiv:2310.20707Yanai Elazar, Akshita Bhagia, Ian Magnusson, et al.2023 · 92 citations
  75. In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space SteeringarXiv:2311.06668Sheng Liu, Haotian Ye, Lei Xing, et al.2023 · 89 citations
  76. MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code GenerationarXiv:2208.08227Federico Cassano, John Gouwar, Daniel Nguyen, et al.2022 · 88 citations
  77. Do Membership Inference Attacks Work on Large Language Models?arXiv:2402.07841Michael Duan, Anshuman Suri, Niloofar Mireshghallah, et al.2024 · 87 citations
  78. The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMsConference on Neural Information Processing Systems (NeurIPS)Laura Ruis, Akbir Khan, Stella Biderman, et al.2022 · 86 citations
  79. In-Context Learning with Long-Context Models: An In-Depth ExplorationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Amanda Bertsch, Maor Ivgi, Emily Xiao, et al.2025 · 81 citations
  80. BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical TextarXiv:2403.18421Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga, et al.2024 · 79 citations
  81. Multilingual Large Language Model: A Survey of Resources, Taxonomy and FrontiersarXiv:2404.04925Libo Qin, Qiguang Chen, Yuhang Zhou, et al.2024 · 75 citations
  82. Structural Persistence in Language Models: Priming as a Window into Abstract Language RepresentationsTransactions of the Association for Computational Linguistics (TACL)Arabella Sinclair, Jaap Jumelet, Willem Zuidema, et al.2022 · 74 citations
  83. Physics of Language Models: Part 3.2, Knowledge ManipulationarXiv:2309.14402Zeyuan Allen-Zhu, Yuanzhi Li2023 · 72 citations
  84. Apertus: Democratizing Open and Compliant LLMs for Global Language EnvironmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.2026 · 68 citations
  85. A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, et al.2023 · 65 citations
  86. Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic TasksarXiv:2305.14201Tiedong Liu, Bryan Kian Hsiang Low2023 · 65 citations
  87. Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use CasesarXiv:2303.14742Yunjie Ji, Yong Deng, Yan Gong, et al.2023 · 62 citations
  88. Rho-1: Not All Tokens Are What You NeedarXiv:2404.07965Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.2024 · 59 citations
  89. Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning ProcessarXiv:2407.20311Tian Ye, Zicheng Xu, Yuanzhi Li, et al.2024 · 58 citations
  90. RegMix: Data Mixture as Regression for Language Model Pre-trainingarXiv:2407.01492Qian Liu, Xiaosen Zheng, Niklas Muennighoff, et al.2024 · 57 citations
  91. On the application of Large Language Models for language teaching and assessment technologyarXiv:2307.08393Andrew Caines, Luca Benedetto, Shiva Taslimipoor, et al.2023 · 51 citations
  92. Getting the most out of your tokenizer for pre-training and domain adaptationarXiv:2402.01035Gautier Dagan, Gabriel Synnaeve, Baptiste Roziere2024 · 47 citations
  93. Language models scale reliably with over-training and on downstream tasksarXiv:2403.08540Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.2024 · 46 citations
  94. Stable LM 2 1.6B Technical ReportarXiv:2402.17834Marco Bellagente, Jonathan Tow, Dakota Mahan, et al.2024 · 46 citations
  95. On Memorization of Large Language Models in Logical ReasoningInternational Joint Conference on Natural Language Processing (IJCNLP)Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.2025 · 45 citations
  96. CoCoMIC: Code Completion by Jointly Modeling In-file and Cross-file ContextLanguage Resources and Evaluation Conference (LREC)Yangruibo Ding, Zijian Wang, Wasi Ahmad, et al.2024 · 45 citations
  97. Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Sander Land, Max Bartolo2024 · 42 citations
  98. Paloma: A Benchmark for Evaluating Language Model FitConference on Neural Information Processing Systems (NeurIPS)Ian Magnusson, Akshita Bhagia, Valentin Hofmann, et al.2023 · 42 citations
  99. Observational Scaling Laws and the Predictability of Language Model PerformancearXiv:2405.10938Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 40 citations
  100. SlimPajama-DC: Understanding Data Combinations for LLM TrainingarXiv:2309.10818Zhiqiang Shen, Tianhua Tao, Liqun Ma, et al.2023 · 38 citations

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