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Who cites Alexander A. Alemi

224 citations of their works from 224 papers of our library (of the 149,439 whose bibliographies we read) · 102 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Alexander A. Alemi

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  1. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,728 citations
  2. Solving Quantitative Reasoning Problems with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Aitor Lewkowycz, Anders Andreassen, David Dohan, et al.2022 · 992 citations
  3. 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
  4. Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-ImprovementarXiv:2409.12122An Yang, Beichen Zhang, Binyuan Hui, et al.2024 · 417 citations
  5. On-Policy Distillation of Language Models: Learning from Self-Generated MistakesarXiv:2306.13649Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.2023 · 299 citations
  6. LeanDojo: Theorem Proving with Retrieval-Augmented Language ModelsConference on Neural Information Processing Systems (NeurIPS)Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.2023 · 253 citations
  7. Generative Language Modeling for Automated Theorem ProvingarXiv:2009.03393Stanislas Polu, Ilya Sutskever2020 · 241 citations
  8. On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A SurveyFindings of the Association for Computational LinguisticsLin Long, Rui Wang, Ruixuan Xiao, et al.2024 · 237 citations
  9. Autoformalization with Large Language ModelsarXiv:2205.12615Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.2022 · 204 citations
  10. 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
  11. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 195 citations
  12. 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
  13. 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
  14. A Survey of Machine Learning for Big Code and NaturalnessACM Computing SurveysMiltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.2017 · 167 citations
  15. Training Language Models to Self-Correct via Reinforcement LearningarXiv:2409.12917Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024 · 159 citations
  16. SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the WildarXiv:2503.18892Weihao Zeng, Yuzhen Huang, Qian Liu, et al.2025 · 154 citations
  17. Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
  18. Generative Verifiers: Reward Modeling as Next-Token PredictionarXiv:2408.15240Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.2024 · 152 citations
  19. Many-Shot In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.2024 · 142 citations
  20. ProofNet: Autoformalizing and Formally Proving Undergraduate-Level MathematicsarXiv:2302.12433Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al.2023 · 142 citations
  21. Deep Network Guided Proof SearchEPiC series in computingSarah Loos, Geoffrey Irving, Christian Szegedy, et al.2017 · 139 citations
  22. 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
  23. Formal Mathematics Statement Curriculum LearningarXiv:2202.01344Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.2022 · 133 citations
  24. Demystifying Long Chain-of-Thought Reasoning in LLMsarXiv:2502.03373Edward Yeo, Yuxuan Tong, Morry Niu, et al.2025 · 119 citations
  25. V-STaR: Training Verifiers for Self-Taught ReasonersarXiv:2402.06457Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024 · 114 citations
  26. Premise Selection for Theorem Proving by Deep Graph EmbeddingarXiv:1709.09994Mingzhe Wang, Yihe Tang, Jian Wang, et al.2017 · 106 citations
  27. GamePad: A Learning Environment for Theorem ProvingarXiv:1806.00608Daniel Huang, Prafulla Dhariwal, Dawn Song, et al.2018 · 94 citations
  28. Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
  29. InternLM-Math: Open Math Large Language Models Toward Verifiable ReasoningarXiv:2402.06332Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.2024 · 90 citations
  30. Learning to Prove Theorems via Interacting with Proof AssistantsarXiv:1905.09381Kaiyu Yang, Jia Deng2019 · 90 citations
  31. Goedel-Prover: A Frontier Model for Open-Source Automated Theorem ProvingarXiv:2502.07640Yong Lin, Shange Tang, Bohan Lyu, et al.2025 · 84 citations
  32. DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-SolvingarXiv:2407.13690Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.2024 · 81 citations
  33. 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
  34. LEGO-Prover: Neural Theorem Proving with Growing LibrariesarXiv:2310.00656Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.2023 · 79 citations
  35. Thor: Wielding Hammers to Integrate Language Models and Automated Theorem ProversarXiv:2205.10893Albert Q. Jiang, Wenda Li, Szymon Tworkowski, et al.2022 · 79 citations
  36. HOList: An Environment for Machine Learning of Higher-Order Theorem ProvingarXiv:1904.03241Kshitij Bansal, Sarah M. Loos, Markus N. Rabe, et al.2019 · 78 citations
  37. NaturalProofs: Mathematical Theorem Proving in Natural LanguagearXiv:2104.01112Sean Welleck, Jiacheng Liu, Ronan Le Bras, et al.2021 · 76 citations
  38. Generating Correctness Proofs with Neural NetworksarXiv:1907.07794Alex Sanchez-Stern, Yousef Alhessi, Lawrence Saul, et al.2019 · 69 citations
  39. Agent Q: Advanced Reasoning and Learning for Autonomous AI AgentsarXiv:2408.07199Pranav Putta, Edmund Mills, Naman Garg, et al.2024 · 68 citations
  40. Modular Pluralism: Pluralistic Alignment via Multi-LLM CollaborationConference on Empirical Methods in Natural Language Processing (EMNLP)Shangbin Feng, Taylor Sorensen, Yuhan Liu, et al.2024 · 68 citations
  41. VinePPO: Refining Credit Assignment in RL Training of LLMsarXiv:2410.01679Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, et al.2024 · 63 citations
  42. Small Models Struggle to Learn from Strong ReasonersFindings of the Association for Computational LinguisticsYuetai Li, Xiang Yue, Zhangchen Xu, et al.2025 · 61 citations
  43. ENIGMA-NG: Efficient Neural and Gradient-Boosted Inference Guidance for ELecture notes in computer scienceKarel Chvalovský, Jan Jakubův, Martin Suda, et al.2019 · 61 citations
  44. MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zimu Lu, Aojun Zhou, Houxing Ren, et al.2024 · 58 citations
  45. Premise Order Matters in Reasoning with Large Language ModelsarXiv:2402.08939Xinyun Chen, Ryan A. Chi, Xuezhi Wang, et al.2024 · 58 citations
  46. Learning Continuous Semantic Representations of Symbolic ExpressionsarXiv:1611.01423Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli, et al.2016 · 57 citations
  47. RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-FoldConference on Neural Information Processing Systems (NeurIPS)Amrith Setlur, Saurabh Garg, Xinyang Geng, et al.2024 · 56 citations
  48. Learning to Prove Theorems by Learning to Generate TheoremsarXiv:2002.07019Mingzhe Wang, Jia Deng2020 · 53 citations
  49. 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
  50. Lean-STaR: Learning to Interleave Thinking and ProvingarXiv:2407.10040Haohan Lin, Zhiqing Sun, Sean Welleck, et al.2024 · 51 citations
  51. Reinforcement Learning of Theorem ProvingarXiv:1805.07563Cezary Kaliszyk, Josef Urban, Henryk Michalewski, et al.2018 · 50 citations
  52. Formal Mathematical Reasoning: A New Frontier in AIarXiv:2412.16075Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.2024 · 49 citations
  53. HolStep: A Machine Learning Dataset for Higher-order Logic Theorem ProvingarXiv:1703.00426Cezary Kaliszyk, François Chollet, Christian Szegedy2017 · 48 citations
  54. Holophrasm: a neural Automated Theorem Prover for higher-order logicarXiv:1608.02644Daniel Whalen2016 · 48 citations
  55. Darwin Godel Machine: Open-Ended Evolution of Self-Improving AgentsarXiv:2505.22954Jenny Zhang, Shengran Hu, Cong Lu, et al.2025 · 47 citations
  56. DeepSeek-R1 Thoughtology: Let's think about LLM ReasoningarXiv:2504.07128Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, et al.2025 · 47 citations
  57. Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-ThoughtarXiv:2501.04682Violet Xiang, Charlie Snell, Kanishk Gandhi, et al.2025 · 47 citations
  58. A Survey on Deep Learning for Theorem ProvingarXiv:2404.09939Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.2024 · 46 citations
  59. Direct Nash Optimization: Teaching Language Models to Self-Improve with General PreferencesarXiv:2404.03715Corby Rosset, Ching-An Cheng, Arindam Mitra, et al.2024 · 44 citations
  60. Premise Selection in Natural Language Mathematical TextsAnnual Meeting of the Association for Computational Linguistics (ACL)Deborah Ferreira, André Freitas2020 · 44 citations
  61. IsarStep: a Benchmark for High-level Mathematical ReasoningarXiv:2006.09265Wenda Li, Lei Yu, Yuhuai Wu, et al.2020 · 43 citations
  62. INT: An Inequality Benchmark for Evaluating Generalization in Theorem ProvingarXiv:2007.02924Yuhuai Wu, Albert Qiaochu Jiang, Jimmy Ba, et al.2020 · 41 citations
  63. DT-Solver: Automated Theorem Proving with Dynamic-Tree Sampling Guided by Proof-level Value FunctionAnnual Meeting of the Association for Computational Linguistics (ACL)Haiming Wang, Ye Yuan, Zhengying Liu, et al.2023 · 40 citations
  64. Lean Copilot: Large Language Models as Copilots for Theorem Proving in LeanarXiv:2404.12534Peiyang Song, Kaiyu Yang, Anima Anandkumar2024 · 39 citations
  65. RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?arXiv:2501.11284Haotian Xu, Xing Wu, Weinong Wang, et al.2025 · 37 citations
  66. Learning to Reason in Large Theories without ImitationarXiv:1905.10501Kshitij Bansal, Christian Szegedy, Markus N. Rabe, et al.2019 · 36 citations
  67. Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning GaparXiv:2402.19450Saurabh Srivastava, Annarose M B, Anto P, et al.2024 · 35 citations
  68. Magnushammer: A Transformer-Based Approach to Premise SelectionarXiv:2303.04488Maciej Mikuła, Szymon Tworkowski, Szymon Antoniak, et al.2023 · 35 citations
  69. AgentGym: Evolving Large Language Model-based Agents across Diverse EnvironmentsarXiv:2406.04151Zhiheng Xi, Yiwen Ding, Wenxiang Chen, et al.2024 · 33 citations
  70. Mathematical Reasoning in Latent SpacearXiv:1909.11851Dennis Lee, Christian Szegedy, Markus N. Rabe, et al.2019 · 33 citations
  71. 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
  72. Property Invariant Embedding for Automated ReasoningFrontiers in artificial intelligence and applicationsMiroslav Olšák, Cezary Kaliszyk, Josef Urban2019 · 30 citations
  73. Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal SamplingarXiv:2408.16737Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.2024 · 27 citations
  74. A Survey on Large Language Models for Mathematical ReasoningACM Computing SurveysPeng-Yuan Wang, Tian-Shuo Liu, Chenyang Wang, et al.2025 · 26 citations
  75. NaturalReasoning: Reasoning in the Wild with 2.8M Challenging QuestionsConference on Neural Information Processing Systems (NeurIPS)Weizhe Yuan, Jane Yu, Song Jiang, et al.2025 · 26 citations
  76. Scaling Test-Time Compute Without Verification or RL is SuboptimalarXiv:2502.12118Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.2025 · 26 citations
  77. Learning Formal Mathematics From Intrinsic MotivationConference on Neural Information Processing Systems (NeurIPS)Gabriel Poesia, David Broman, Nick Haber, et al.2024 · 23 citations
  78. MiniCPM4: Ultra-Efficient LLMs on End DevicesarXiv:2506.07900MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.2025 · 22 citations
  79. ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process RewardingInternational ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)Zhongxiang Sun, Qipeng Wang, Weijie Yu, et al.2025 · 22 citations
  80. Stateful Premise Selection by Recurrent Neural NetworksEPiC series in computingBartosz Piotrowski, Josef Urban2020 · 21 citations
  81. miniCTX: Neural Theorem Proving with (Long-)ContextsarXiv:2408.03350Jiewen Hu, Thomas Zhu, Sean Welleck2024 · 18 citations
  82. Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language ModelsarXiv:2412.02980Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.2024 · 17 citations
  83. Can Large Reasoning Models Self-Train?arXiv:2505.21444Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.2025 · 16 citations
  84. Solving Formal Math Problems by Decomposition and Iterative ReflectionarXiv:2507.15225Yichi Zhou, Jianqiu Zhao, Yongxin Zhang, et al.2025 · 16 citations
  85. Guiding High-Performance SAT Solvers with Unsat-Core PredictionsarXiv:1903.04671 (International Conference on Theory and Applications of Satisfiability Testing. Springer, Cham, 2019)Daniel Selsam, Nikolaj Bjørner2019 · 16 citations
  86. Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Fangzhi Xu, Qiushi Sun, Kanzhi Cheng, et al.2025 · 15 citations
  87. Prover Agent: An Agent-Based Framework for Formal Mathematical ProofsarXiv:2506.19923Kaito Baba, Chaoran Liu, Shuhei Kurita, et al.2025 · 14 citations
  88. Mastering Board Games by External and Internal Planning with Language ModelsarXiv:2412.12119John Schultz, Jakub Adamek, Matej Jusup, et al.2024 · 14 citations
  89. Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive SearcharXiv:2502.02508Maohao Shen, Guangtao Zeng, Zhenting Qi, et al.2025 · 13 citations
  90. Algorithm Discovery With LLMs: Evolutionary Search Meets Reinforcement LearningarXiv:2504.05108Anja Surina, Amin Mansouri, Lars Quaedvlieg, et al.2025 · 12 citations
  91. Learning Heuristics for Quantified Boolean Formulas through Deep Reinforcement LearningarXiv:1807.08058Gil Lederman, Markus N. Rabe, Edward A. Lee, et al.2018 · 12 citations
  92. Progress or Regress? Self-Improvement Reversal in Post-trainingarXiv:2407.05013Ting Wu, Xuefeng Li, Pengfei Liu2024 · 10 citations
  93. Ax-Prover: A Deep Reasoning Agentic Framework for Theorem Proving in Mathematics and Quantum PhysicsarXiv:2510.12787Benjamin Breen, Marco Del Tredici, Jacob McCarran, et al.2025 · 9 citations
  94. HS-STaR: Hierarchical Sampling for Self-Taught Reasoners via Difficulty Estimation and Budget ReallocationConference on Empirical Methods in Natural Language Processing (EMNLP)Feng Xiong, Hongling Xu, Yifei Wang, et al.2025 · 9 citations
  95. To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-MaximizationFindings of the Association for Computational LinguisticsHaozhe Wang, Long Li, Chao Qu, et al.2025 · 9 citations
  96. Superficial Self-Improved Reasoners Benefit from Model MergingConference on Empirical Methods in Natural Language Processing (EMNLP)Xiangchi Yuan, Chunhui Zhang, Zheyuan Liu, et al.2025 · 8 citations
  97. Enhancing Auto-regressive Chain-of-Thought through Loop-Aligned ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Qifan Yu, Zhenyu He, Sijie Li, et al.2026 · 5 citations
  98. MPS-Prover: Advancing Stepwise Theorem Proving by Multi-Perspective Search and Data CurationConference on Neural Information Processing Systems (NeurIPS)Zhenwen Liang, Linfeng Song, Yang Li, et al.2025 · 4 citations
  99. An Iterative Utility Judgment Framework Inspired by Philosophical Relevance via LLMsFindings of the Association for Computational LinguisticsHengran Zhang, Keping Bi, Jiafeng Guo, et al.2026
  100. Decoupling Generalization and Adaptation in Meta-Learning for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Nitin Vetcha, Binqian Xu, Dianbo Liu2026

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