Elamur Research⌕
☰
home / authors / Ramana Kumar / cited by

Who cites Ramana Kumar

371 citations of their works from 370 papers of our library (of the 149,439 whose bibliographies we read) · 164 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Ramana Kumar

1 2

  1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  2. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,728 citations
  3. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  4. 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
  5. Let's Verify Step by SteparXiv:2305.20050Hunter Lightman, Vineet Kosaraju, Yura Burda, et al.2023 · 1,412 citations
  6. OpenAI o1 System CardarXiv:2412.16720OpenAI, Aaron Jaech, Adam Kalai, et al.2024 · 1,110 citations
  7. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic CapabilitiesarXiv:2507.06261Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.2025 · 974 citations
  8. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and BeyondACM Transactions on Knowledge Discovery from DataJingfeng Yang, Hongye Jin, Ruixiang Tang, et al.2023 · 814 citations
  9. Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought PromptingConference on Neural Information Processing Systems (NeurIPS)Miles Turpin, Julian Michael, Ethan Perez, et al.2023 · 586 citations
  10. Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model ParametersarXiv:2408.03314Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.2024 · 567 citations
  11. Unleashing the potential of prompt engineering for large language modelsarXiv:2310.14735 · Patterns 6(6) 101,260 (2025)Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.2023 · 536 citations
  12. Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human AnnotationsAnnual Meeting of the Association for Computational Linguistics (ACL)Peiyi Wang, Lei Li, Zhihong Shao, et al.2024 · 497 citations
  13. AlpacaFarm: A Simulation Framework for Methods that Learn from Human FeedbackConference on Neural Information Processing Systems (NeurIPS)Yann Dubois, Xuechen Li, Rohan Taori, et al.2023 · 456 citations
  14. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructarXiv:2308.09583Haipeng Luo, Qingfeng Sun, Can Xu, et al.2023 · 372 citations
  15. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  16. Llemma: An Open Language Model For MathematicsarXiv:2310.10631Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.2023 · 286 citations
  17. Scaling Relationship on Learning Mathematical Reasoning with Large Language ModelsarXiv:2308.01825Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.2023 · 261 citations
  18. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 256 citations
  19. Reinforced Self-Training (ReST) for Language ModelingarXiv:2308.08998Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.2023 · 224 citations
  20. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
  21. Autoformalization with Large Language ModelsarXiv:2205.12615Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.2022 · 204 citations
  22. 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
  23. Baldur: Whole-Proof Generation and Repair with Large Language ModelsarXiv:2303.04910Emily First, Markus N. Rabe, Talia Ringer, et al.2023 · 175 citations
  24. Improve Mathematical Reasoning in Language Models by Automated Process SupervisionarXiv:2406.06592Liangchen Luo, Yinxiao Liu, Rosanne Liu, et al.2024 · 168 citations
  25. The Lessons of Developing Process Reward Models in Mathematical ReasoningFindings of the Association for Computational LinguisticsZhenru Zhang, Chujie Zheng, Yangzhen Wu, et al.2025 · 161 citations
  26. 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
  27. Training Language Models to Self-Correct via Reinforcement LearningarXiv:2409.12917Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024 · 159 citations
  28. Stop Overthinking: A Survey on Efficient Reasoning for Large Language ModelsarXiv:2503.16419Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.2025 · 157 citations
  29. Generative Verifiers: Reward Modeling as Next-Token PredictionarXiv:2408.15240Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.2024 · 152 citations
  30. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
  31. Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 149 citations
  32. 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
  33. ReFT: Reasoning with Reinforced Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Luong Trung, Xinbo Zhang, Zhanming Jie, et al.2024 · 134 citations
  34. The WMDP Benchmark: Measuring and Reducing Malicious Use With UnlearningarXiv:2403.03218Nathaniel Li, Alexander Pan, Anjali Gopal, et al.2024 · 127 citations
  35. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and FuturearXiv:2309.15402Zheng Chu, Jingchang Chen, Qianglong Chen, et al.2023 · 125 citations
  36. CRUXEval: A Benchmark for Code Reasoning, Understanding and ExecutionarXiv:2401.03065Alex Gu, Baptiste Rozière, Hugh Leather, et al.2024 · 122 citations
  37. 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
  38. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 122 citations
  39. Deliberative Alignment: Reasoning Enables Safer Language ModelsSuperIntelligence - Robotics - Safety & AlignmentMelody Y. Guan, Manas Joglekar, Eric Wallace, et al.2024 · 115 citations
  40. V-STaR: Training Verifiers for Self-Taught ReasonersarXiv:2402.06457Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024 · 114 citations
  41. Can LLM-Generated Misinformation Be Detected?arXiv:2309.13788Canyu Chen, Kai Shu2023 · 108 citations
  42. JudgeBench: A Benchmark for Evaluating LLM-based JudgesarXiv:2410.12784Sijun Tan, Siyuan Zhuang, Kyle Montgomery, et al.2024 · 101 citations
  43. Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
  44. Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language ModelsarXiv:2503.06749Wenxuan Huang, Bohan Jia, Zijie Zhai, et al.2025 · 92 citations
  45. InternLM-Math: Open Math Large Language Models Toward Verifiable ReasoningarXiv:2402.06332Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.2024 · 90 citations
  46. Learning to Prove Theorems via Interacting with Proof AssistantsarXiv:1905.09381Kaiyu Yang, Jia Deng2019 · 90 citations
  47. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  48. O1 Replication Journey: A Strategic Progress Report — Part 1arXiv:2410.18982Yiwei Qin, Xuefeng Li, Haoyang Zou, et al.2024 · 86 citations
  49. Evaluating Mathematical Reasoning Beyond AccuracyProceedings of the AAAI Conference on Artificial IntelligenceShijie Xia, Xuefeng Li, Yixin Liu, et al.2024 · 85 citations
  50. Proof Artifact Co-training for Theorem Proving with Language ModelsarXiv:2102.06203Jesse Michael Han, Jason Rute, Yuhuai Wu, et al.2021 · 82 citations
  51. Interpretability at Scale: Identifying Causal Mechanisms in AlpacaConference on Neural Information Processing Systems (NeurIPS)Zhengxuan Wu, Atticus Geiger, Thomas Icard, et al.2023 · 81 citations
  52. Toward Self-Improvement of LLMs via Imagination, Searching, and CriticizingConference on Neural Information Processing Systems (NeurIPS)Ye Tian, Baolin Peng, Linfeng Song, et al.2024 · 80 citations
  53. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
  54. OVM, Outcome-supervised Value Models for Planning in Mathematical ReasoningFindings of the Association for Computational LinguisticsFei Yu, Anningzhe Gao, Benyou Wang2023 · 78 citations
  55. Recursive Introspection: Teaching Language Model Agents How to Self-ImproveConference on Neural Information Processing Systems (NeurIPS)Yuxiao Qu, Tianjun Zhang, Naman Garg, et al.2024 · 75 citations
  56. Cumulative Reasoning with Large Language ModelsarXiv:2308.04371Yifan Zhang, Jingqin Yang, Yang Yuan, et al.2023 · 74 citations
  57. Agent Q: Advanced Reasoning and Learning for Autonomous AI AgentsarXiv:2408.07199Pranav Putta, Edmund Mills, Naman Garg, et al.2024 · 68 citations
  58. Routing to the Expert: Efficient Reward-guided Ensemble of Large Language ModelsarXiv:2311.08692Keming Lu, Hongyi Yuan, Runji Lin, et al.2023 · 66 citations
  59. Monitoring Reasoning Models for Misbehavior and the Risks of Promoting ObfuscationarXiv:2503.11926Bowen Baker, Joost Huizinga, Leo Gao, et al.2025 · 63 citations
  60. PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mingyang Song, Zhaochen Su, Xiaoye Qu, et al.2025 · 63 citations
  61. VinePPO: Refining Credit Assignment in RL Training of LLMsarXiv:2410.01679Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, et al.2024 · 63 citations
  62. Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMsarXiv:2506.14245Xumeng Wen, Zihan Liu, Shun Zheng, et al.2025 · 62 citations
  63. Teaching Large Language Models to Reason with Reinforcement LearningarXiv:2403.04642Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.2024 · 61 citations
  64. Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in ChinchillaarXiv:2307.09458Tom Lieberum, Matthew Rahtz, Janos Kramar, et al.2023 · 58 citations
  65. Teaching Arithmetic to Small TransformersarXiv:2307.03381Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, et al.2023 · 57 citations
  66. OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AIConference on Neural Information Processing Systems (NeurIPS)Zhen Huang, Zengzhi Wang, Shijie Xia, et al.2024 · 56 citations
  67. Parsel: Algorithmic Reasoning with Language Models by Composing DecompositionsConference on Neural Information Processing Systems (NeurIPS)Eric Zelikman, Qian Huang, Gabriel Poesia, et al.2023 · 56 citations
  68. Q*: Improving Multi-step Reasoning for LLMs with Deliberative PlanningarXiv:2406.14283Chaojie Wang, Yanchen Deng, Zhiyi Lyu, et al.2024 · 53 citations
  69. Easy-to-Hard Generalization: Scalable Alignment Beyond Human SupervisionConference on Neural Information Processing Systems (NeurIPS)Zhiqing Sun, Longhui Yu, Yikang Shen, et al.2024 · 51 citations
  70. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
  71. OpenR: An Open Source Framework for Advanced Reasoning with Large Language ModelsarXiv:2410.09671Jun Wang, Meng Fang, Ziyu Wan, et al.2024 · 50 citations
  72. LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical ReasoningarXiv:2410.02884Di Zhang, Jianbo Wu, Jingdi Lei, et al.2024 · 49 citations
  73. A Survey on Deep Learning for Theorem ProvingarXiv:2404.09939Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.2024 · 46 citations
  74. ARGS: Alignment as Reward-Guided SearcharXiv:2402.01694Maxim Khanov, Jirayu Burapacheep, Yixuan Li2024 · 46 citations
  75. Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decodingarXiv:2309.15028Jiacheng Liu, Andrew Cohen, Ramakanth Pasunuru, et al.2023 · 46 citations
  76. GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local RefinementsarXiv:2402.10963Alex Havrilla, Sharath Raparthy, Christoforus Nalmpantis, et al.2024 · 45 citations
  77. TinyGSM: achieving >80% on GSM8k with small language modelsarXiv:2312.09241Bingbin Liu, Sebastien Bubeck, Ronen Eldan, et al.2023 · 45 citations
  78. Entropy-Aware On-Policy Distillation of Language ModelsarXiv:2603.07079Woogyeol Jin, Taywon Min, Yongjin Yang, et al.2026 · 44 citations
  79. Augmenting Math Word Problems via Iterative Question ComposingProceedings of the AAAI Conference on Artificial IntelligenceHaoxiong Liu, Yifan Zhang, Yifan Luo, et al.2024 · 44 citations
  80. Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process SupervisionFindings of the Association for Computational LinguisticsZihan Wang, Yunxuan Li, Yuexin Wu, et al.2024 · 43 citations
  81. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
  82. DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language ModelsarXiv:2411.00836Chengke Zou, Xingang Guo, Rui Yang, et al.2024 · 41 citations
  83. GPT Can Solve Mathematical Problems Without a CalculatorarXiv:2309.03241Zhen Yang, Ming Ding, Qingsong Lv, et al.2023 · 41 citations
  84. INT: An Inequality Benchmark for Evaluating Generalization in Theorem ProvingarXiv:2007.02924Yuhuai Wu, Albert Qiaochu Jiang, Jimmy Ba, et al.2020 · 41 citations
  85. Let's reward step by step: Step-Level reward model as the Navigators for ReasoningarXiv:2310.10080Qianli Ma, Haotian Zhou, Tingkai Liu, et al.2023 · 40 citations
  86. A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic SystemsarXiv:2504.09037Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.2025 · 39 citations
  87. LIME: Learning Inductive Bias for Primitives of Mathematical ReasoningarXiv:2101.06223Yuhuai Wu, Markus Rabe, Wenda Li, et al.2021 · 39 citations
  88. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
  89. AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward ModelingFindings of the Association for Computational LinguisticsZihan Liu, Yang Chen, Mohammad Shoeybi, et al.2025 · 37 citations
  90. Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn'tarXiv:2503.16219Quy-Anh Dang, Chris Ngo2025 · 37 citations
  91. A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to ReproducibilityarXiv:2504.07086Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao, et al.2025 · 36 citations
  92. Measuring AI Ability to Complete Long Software TasksConference on Neural Information Processing Systems (NeurIPS)Thomas Kwa, Ben West, Joel Becker, et al.2025 · 36 citations
  93. Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement LearningarXiv:2402.05808Zhiheng Xi, Wenxiang Chen, Boyang Hong, et al.2024 · 36 citations
  94. Self-Refine Instruction-Tuning for Aligning Reasoning in Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Leonardo Ranaldi, Andre Freitas2024 · 35 citations
  95. Echo Chamber: RL Post-training Amplifies Behaviors Learned in PretrainingarXiv:2504.07912Rosie Zhao, Alexandru Meterez, Sham Kakade, et al.2025 · 34 citations
  96. mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Huiyuan Lai, Malvina Nissim2024 · 34 citations
  97. Process-Driven Autoformalization in Lean 4arXiv:2406.01940Jianqiao Lu, Yingjia Wan, Zhengying Liu, et al.2024 · 33 citations
  98. StepCoder: Improving Code Generation with Reinforcement Learning from Compiler FeedbackAnnual Meeting of the Association for Computational Linguistics (ACL)Shihan Dou, Yan Liu, Haoxiang Jia, et al.2024 · 32 citations
  99. Learning Planning-based Reasoning by Trajectories Collection and Process Reward SynthesizingConference on Empirical Methods in Natural Language Processing (EMNLP)Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, et al.2024 · 31 citations
  100. NExT: Teaching Large Language Models to Reason about Code ExecutionarXiv:2404.14662Ansong Ni, Miltiadis Allamanis, Arman Cohan, et al.2024 · 30 citations

1 2

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/ramana-kumar/cited-by/