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Who cites Milad Aghajohari

109 citations of their works from 108 papers of our library (of the 149,439 whose bibliographies we read) · 43 with a page here, the most cited first · ← Milad Aghajohari

  1. DAPO: An Open-Source LLM Reinforcement Learning System at ScalearXiv:2503.14476Qiying Yu, Zheng Zhang, Ruofei Zhu, et al.2025 · 668 citations
  2. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  3. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
  4. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  5. Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRsarXiv:2503.01307Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.2025 · 123 citations
  6. 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
  7. Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
  8. 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
  9. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
  10. DeepSeek-R1 Thoughtology: Let's think about LLM ReasoningarXiv:2504.07128Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, et al.2025 · 47 citations
  11. 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
  12. 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
  13. 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
  14. Echo Chamber: RL Post-training Amplifies Behaviors Learned in PretrainingarXiv:2504.07912Rosie Zhao, Alexandru Meterez, Sham Kakade, et al.2025 · 34 citations
  15. T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference ScalingarXiv:2501.11651Zhenyu Hou, Xin Lv, Rui Lu, et al.2025 · 28 citations
  16. A Survey on Large Language Models for Mathematical ReasoningACM Computing SurveysPeng-Yuan Wang, Tian-Shuo Liu, Chenyang Wang, et al.2025 · 26 citations
  17. Scaling Test-Time Compute Without Verification or RL is SuboptimalarXiv:2502.12118Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.2025 · 26 citations
  18. Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy DistillationarXiv:2604.13010Yecheng Wu, Song Han, Han Cai2026 · 10 citations
  19. Guiding Reasoning in Small Language Models with LLM AssistancearXiv:2504.09923Yujin Kim, Euiin Yi, Minu Kim, et al.2025 · 9 citations
  20. Self-Distilled Policy GradientarXiv:2606.04036Yifeng Liu, Shiyuan Zhang, Yifan Zhang, et al.2026 · 5 citations
  21. What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoTarXiv:2509.19284Yunzhen Feng, Julia Kempe, Cheng Zhang, et al.2025 · 4 citations
  22. Language Specific Knowledge: Do Models Know Better in X than in English?arXiv:2505.14990Ishika Agarwal, Nimet Beyza Bozdag, Dilek Hakkani-Tur2025 · 1 citation

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