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Who cites Srini Iyer

2,273 citations of their works from 2,085 papers of our library (of the 149,439 whose bibliographies we read) · 477 with a page here, the most cited first · page 2 of 5 · 101–200 · ← Srini Iyer

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  1. 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
  2. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
  3. 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
  4. RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Cheng Niu, Yuanhao Wu, Juno Zhu, et al.2024 · 207 citations
  5. Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2arXiv:2311.10702Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.2023 · 207 citations
  6. Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Oded Ovadia, Menachem Brief, Moshik Mishaeli, et al.2024 · 206 citations
  7. Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 202 citations
  8. Model Tells You What to Discard: Adaptive KV Cache Compression for LLMsarXiv:2310.01801Suyu Ge, Yunan Zhang, Liyuan Liu, et al.2023 · 202 citations
  9. 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
  10. 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
  11. Towards Faithful Model Explanation in NLP: A SurveyComputational LinguisticsQing Lyu, Marianna Apidianaki, Chris Callison-Burch2024 · 197 citations
  12. Retrieval Augmented Code Generation and SummarizationFindings of the Association for Computational LinguisticsMd Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, et al.2021 · 193 citations
  13. Densely Connected Graph Convolutional Networks for Graph-to-Sequence LearningTransactions of the Association for Computational Linguistics (TACL)Zhijiang Guo, Yan Zhang, Zhiyang Teng, et al.2019 · 193 citations
  14. LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local RelationsAnnual Meeting of the Association for Computational Linguistics (ACL)Ruisheng Cao, Lu Chen, Zhi Chen, et al.2021 · 191 citations
  15. CodeS: Towards Building Open-source Language Models for Text-to-SQLarXiv:2402.16347Haoyang Li, Jing Zhang, Hanbing Liu, et al.2024 · 190 citations
  16. Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, et al.2022 · 190 citations
  17. Preference Ranking Optimization for Human AlignmentProceedings of the AAAI Conference on Artificial IntelligenceFeifan Song, Bowen Yu, Minghao Li, et al.2023 · 188 citations
  18. RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language ModelsarXiv:2310.00746Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al.2023 · 187 citations
  19. Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 182 citations
  20. ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated CasesarXiv:2306.05301Qiaoyu Tang, Ziliang Deng, Hongyu Lin, et al.2023 · 180 citations
  21. LESS: Selecting Influential Data for Targeted Instruction TuningarXiv:2402.04333Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, et al.2024 · 178 citations
  22. What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction TuningarXiv:2312.15685Wei Liu, Weihao Zeng, Keqing He, et al.2023 · 178 citations
  23. Editing-Based SQL Query Generation for Cross-Domain Context-Dependent QuestionsConference on Empirical Methods in Natural Language Processing (EMNLP)Rui Zhang, Tao Yu, Heyang Er, et al.2019 · 177 citations
  24. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
  25. Aligning Large Multimodal Models with Factually Augmented RLHFarXiv:2309.14525Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.2023 · 176 citations
  26. OpenChat: Advancing Open-source Language Models with Mixed-Quality DataarXiv:2309.11235Guan Wang, Sijie Cheng, Xianyuan Zhan, et al.2023 · 174 citations
  27. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
  28. Generative Representational Instruction TuningarXiv:2402.09906Niklas Muennighoff, Hongjin Su, Liang Wang, et al.2024 · 172 citations
  29. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
  30. Quark: Controllable Text Generation with Reinforced UnlearningConference on Neural Information Processing Systems (NeurIPS)Ximing Lu, Sean Welleck, Jack Hessel, et al.2022 · 170 citations
  31. A Comprehensive Exploration on WikiSQL with Table-Aware Word ContextualizationarXiv:1902.01069Wonseok Hwang, Jinyeong Yim, Seunghyun Park, et al.2019 · 170 citations
  32. Catastrophic Jailbreak of Open-source LLMs via Exploiting GenerationarXiv:2310.06987Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.2023 · 169 citations
  33. Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4Conference on Empirical Methods in Natural Language Processing (EMNLP)Kent K. Chang, Mackenzie Cramer, Sandeep Soni, et al.2023 · 169 citations
  34. Simple Entity-Centric Questions Challenge Dense RetrieversConference on Empirical Methods in Natural Language Processing (EMNLP)Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, et al.2021 · 169 citations
  35. GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via CipherarXiv:2308.06463Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.2023 · 168 citations
  36. AMR Parsing via Graph-Sequence Iterative InferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Deng Cai, Wai Lam2020 · 168 citations
  37. SantaCoder: don't reach for the stars!arXiv:2301.03988Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al.2023 · 167 citations
  38. Structure-Grounded Pretraining for Text-to-SQLConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al.2021 · 167 citations
  39. Abstract Meaning Representation for Multi-Document SummarizationInternational Conference on Computational Linguistics (COLING)Kexin Liao, Logan Lebanoff, Fei Liu2018 · 167 citations
  40. A Survey of Machine Learning for Big Code and NaturalnessACM Computing SurveysMiltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.2017 · 167 citations
  41. Language Models as Agent ModelsFindings of the Association for Computational LinguisticsJacob Andreas2022 · 165 citations
  42. When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMsTransactions of the Association for Computational Linguistics (TACL)Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.2024 · 161 citations
  43. From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction TuningarXiv:2308.12032Ming Li, Yong Zhang, Zhitao Li, et al.2023 · 161 citations
  44. SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-trainingarXiv:2501.17161Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.2025 · 160 citations
  45. FacTool: Factuality Detection in Generative AI — A Tool Augmented Framework for Multi-Task and Multi-Domain ScenariosarXiv:2307.13528I-Chun Chern, Steffi Chern, Shiqi Chen, et al.2023 · 160 citations
  46. Chameleon: Mixed-Modal Early-Fusion Foundation ModelsarXiv:2405.09818Chameleon Team2024 · 159 citations
  47. Semantic Neural Machine Translation Using AMRLinfeng Song, Daniel Gildea, Yue Zhang, et al.2019 · 159 citations
  48. LLM-based NLG Evaluation: Current Status and ChallengesComputational LinguisticsMingqi Gao, Xinyu Hu, Xunjian Yin, et al.2025 · 153 citations
  49. Graph Pre-training for AMR Parsing and GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Xuefeng Bai, Yulong Chen, Yue Zhang2022 · 153 citations
  50. Investigating Pretrained Language Models for Graph-to-Text GenerationWorkshop on Natural Language Processing for Conversational AILeonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, et al.2021 · 151 citations
  51. CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding ChallengesAnnual Meeting of the Association for Computational Linguistics (ACL)Kechi Zhang, Jia Li, Ge Li, et al.2024 · 150 citations
  52. The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context LearningarXiv:2312.01552Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.2023 · 150 citations
  53. A Review on Language Models as Knowledge BasesarXiv:2204.06031Badr AlKhamissi, Millicent Li, Asli Celikyilmaz, et al.2022 · 150 citations
  54. Evaluating Correctness and Faithfulness of Instruction-Following Models for Question AnsweringTransactions of the Association for Computational Linguistics (TACL)Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lu, et al.2024 · 149 citations
  55. RA-DIT: Retrieval-Augmented Dual Instruction TuningarXiv:2310.01352Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.2023 · 149 citations
  56. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
  57. GPT4Tools: Teaching Large Language Model to Use Tools via Self-instructionConference on Neural Information Processing Systems (NeurIPS)Rui Yang, Lin Song, Yanwei Li, et al.2023 · 147 citations
  58. UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question AnsweringFindings of the Association for Computational LinguisticsBarlas Oguz, Xilun Chen, Vladimir Karpukhin, et al.2022 · 147 citations
  59. PMC-LLaMA: Towards Building Open-source Language Models for MedicinearXiv:2304.14454Chaoyi Wu, Weixiong Lin, Xiaoman Zhang, et al.2023 · 146 citations
  60. How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data CompositionAnnual Meeting of the Association for Computational Linguistics (ACL)Guanting Dong, Hongyi Yuan, Keming Lu, et al.2024 · 145 citations
  61. JudgeLM: Fine-tuned Large Language Models are Scalable JudgesarXiv:2310.17631Lianghui Zhu, Xinggang Wang, Xinlong Wang2023 · 145 citations
  62. MiniLLM: On-Policy Distillation of Large Language ModelsarXiv:2306.08543Yuxian Gu, Li Dong, Furu Wei, et al.2023 · 144 citations
  63. SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked PrefillsarXiv 2023Amey Agrawal, Ashish Panwar, Jayashree Mohan, et al.2023 · 144 citations
  64. Towards Robustness of Text-to-SQL Models against Synonym SubstitutionAnnual Meeting of the Association for Computational Linguistics (ACL)Yujian Gan, Xinyun Chen, Qiuping Huang, et al.2021 · 143 citations
  65. Many-Shot In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.2024 · 142 citations
  66. 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
  67. Diverse Demonstrations Improve In-context Compositional GeneralizationAnnual Meeting of the Association for Computational Linguistics (ACL)Itay Levy, Ben Bogin, Jonathan Berant2023 · 141 citations
  68. 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
  69. Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction StrategiesTransactions of the Association for Computational Linguistics (TACL)Liangming Pan, Michael Saxon, Wenda Xu, et al.2024 · 140 citations
  70. Self-Alignment with Instruction BacktranslationarXiv:2308.06259Xian Li, Ping Yu, Chunting Zhou, et al.2023 · 139 citations
  71. RAFT: Adapting Language Model to Domain Specific RAGarXiv:2403.10131Tianjun Zhang, Shishir G. Patil, Naman Jain, et al.2024 · 137 citations
  72. Mapping Natural Language Instructions to Mobile UI Action SequencesAnnual Meeting of the Association for Computational Linguistics (ACL)Yang Li, Jiacong He, Xin Zhou, et al.2020 · 137 citations
  73. Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning RepresentationsComputational Linguistics in the Netherlands JournalRik van Noord, Johan Bos2017 · 137 citations
  74. InFoBench: Evaluating Instruction Following Ability in Large Language ModelsFindings of the Association for Computational LinguisticsYiwei Qin, Kaiqiang Song, Yebowen Hu, et al.2024 · 136 citations
  75. 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
  76. The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Hannah Rose Kirk, Alexander Whitefield, Paul Rottger, et al.2024 · 133 citations
  77. Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented DialogueAnnual Meeting of the Association for Computational Linguistics (ACL)Anusha Balakrishnan, Jinfeng Rao, Kartikeya Upasani, et al.2019 · 133 citations
  78. Natural Language Reasoning, A SurveyACM Computing SurveysFei Yu, Hongbo Zhang, Prayag Tiwari, et al.2023 · 130 citations
  79. Evaluating the Moral Beliefs Encoded in LLMsConference on Neural Information Processing Systems (NeurIPS)Nino Scherrer, Claudia Shi, Amir Feder, et al.2023 · 129 citations
  80. SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware DecodingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 127 citations
  81. LEVER: Learning to Verify Language-to-Code Generation with ExecutionarXiv:2302.08468Ansong Ni, Srini Iyer, Dragomir Radev, et al.2023 · 126 citations
  82. Generative Judge for Evaluating AlignmentarXiv:2310.05470Junlong Li, Shichao Sun, Weizhe Yuan, et al.2023 · 125 citations
  83. Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-steparXiv:2402.16906Li Zhong, Zilong Wang, Jingbo Shang2024 · 124 citations
  84. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  85. Unlearn What You Want to Forget: Efficient Unlearning for LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaao Chen, Diyi Yang2023 · 124 citations
  86. Broad-Coverage Semantic Parsing as TransductionConference on Empirical Methods in Natural Language Processing (EMNLP)Sheng Zhang, Xutai Ma, Kevin Duh, et al.2019 · 124 citations
  87. FAST: Efficient Action Tokenization for Vision-Language-Action ModelsarXiv:2501.09747Karl Pertsch, Kyle Stachowicz, Brian Ichter, et al.2025 · 123 citations
  88. Mini-Gemini: Mining the Potential of Multi-modality Vision Language ModelsIEEE Transactions on Pattern Analysis and Machine IntelligenceYanwei Li, Yuechen Zhang, Chengyao Wang, et al.2024 · 123 citations
  89. Exploring Underexplored Limitations of Cross-Domain Text-to-SQL GeneralizationConference on Empirical Methods in Natural Language Processing (EMNLP)Yujian Gan, Xinyun Chen, Matthew Purver2021 · 123 citations
  90. CRUXEval: A Benchmark for Code Reasoning, Understanding and ExecutionarXiv:2401.03065Alex Gu, Baptiste Rozière, Hugh Leather, et al.2024 · 122 citations
  91. Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language ModelsarXiv:2501.09686Fengli Xu, Qianyue Hao, Zefang Zong, et al.2025 · 120 citations
  92. Hallucination of Multimodal Large Language Models: A SurveyarXiv:2404.18930Zechen Bai, Pichao Wang, Tianjun Xiao, et al.2024 · 120 citations
  93. #InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language ModelsarXiv:2308.07074Keming Lu, Hongyi Yuan, Zheng Yuan, et al.2023 · 120 citations
  94. A Real-World WebAgent with Planning, Long Context Understanding, and Program SynthesisarXiv:2307.12856Izzeddin Gur, Hiroki Furuta, Austin Huang, et al.2023 · 120 citations
  95. Compositional Exemplars for In-context LearningarXiv:2302.05698Jiacheng Ye, Zhiyong Wu, Jiangtao Feng, et al.2023 · 120 citations
  96. SaulLM-7B: A pioneering Large Language Model for LawarXiv:2403.03883Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, et al.2024 · 119 citations
  97. Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question AnsweringarXiv:2306.04136Jinheon Baek, Alham Fikri Aji, Amir Saffari2023 · 119 citations
  98. Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation ExtractorsFindings of the Association for Computational LinguisticsKai Zhang, Bernal Jimenez Gutierrez, Yu Su2023 · 118 citations
  99. The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Seungone Kim, Se Joo, Doyoung Kim, et al.2023 · 118 citations
  100. Platypus: Quick, Cheap, and Powerful Refinement of LLMsarXiv:2308.07317Ariel N. Lee, Cole J. Hunter, Nataniel Ruiz2023 · 117 citations

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