---
title: "Who cites Milad Aghajohari — 108 papers of our library"
description: "108 papers of the Elamur Research library cite the works of Milad Aghajohari, found in their bibliographies; the most cited first."
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---
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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](https://md.research.elamur.ai/free/en/authors/milad-aghajohari/)

1. [**DAPO: An Open-Source LLM Reinforcement Learning System at Scale arXiv:2503.14476**Qiying Yu, Zheng Zhang, Ruofei Zhu, et al.*2025 · 668 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-dapo-open-source-llm-reinforcement/)
2. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
3. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
4. [**Process Reinforcement through Implicit Rewards arXiv:2502.01456**Ganqu Cui, Lifan Yuan, Zefan Wang, et al.*2025 · 151 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-process-reinforcement-through-implicit-rewards/)
5. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
6. [**Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs arXiv:2503.01307**Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.*2025 · 123 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/)
7. [**Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models arXiv:2501.09686**Fengli Xu, Qianyue Hao, Zefang Zong, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-towards-large-reasoning-models-survey/)
8. **[The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity](https://md.research.elamur.ai/free/en/papers/shojaee-2025-illusion-thinking-understanding-strengths-limitations/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.*2025 · 104 citations*
9. [**Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning arXiv:2410.08146**Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.*2024 · 93 citations*](https://md.research.elamur.ai/free/en/papers/setlur-2024-rewarding-progress-scaling-automated-process/)
10. **[Reinforcement Learning for Reasoning in Large Language Models with One Training Example](https://md.research.elamur.ai/free/en/papers/wang-2025-reinforcement-learning-reasoning-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yiping Wang, Qing Yang, Zhiyuan Zeng, et al.*2025 · 87 citations*
11. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/)
12. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
13. **[Group-in-Group Policy Optimization for LLM Agent Training](https://md.research.elamur.ai/free/en/papers/feng-2025-group-group-policy-optimization-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lang Feng, Zhenghai Xue, Tingcong Liu, et al.*2025 · 69 citations*
14. [**DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning arXiv:2504.07128**Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, et al.*2025 · 47 citations*](https://md.research.elamur.ai/free/en/papers/marjanovic-2025-deepseek-r1-thoughtology-let-s/)
15. [**Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought arXiv:2501.04682**Violet Xiang, Charlie Snell, Kanishk Gandhi, et al.*2025 · 47 citations*](https://md.research.elamur.ai/free/en/papers/xiang-2025-towards-system-2-reasoning-llms/)
16. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/)
17. [**A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility arXiv:2504.07086**Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao, et al.*2025 · 36 citations*](https://md.research.elamur.ai/free/en/papers/hochlehnert-2025-sober-look-progress-language-model/)
18. [**Echo Chamber: RL Post-training Amplifies Behaviors Learned in Pretraining arXiv:2504.07912**Rosie Zhao, Alexandru Meterez, Sham Kakade, et al.*2025 · 34 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-echo-chamber-rl-post-training/)
19. [**T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling arXiv:2501.11651**Zhenyu Hou, Xin Lv, Rui Lu, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/hou-2025-t1-advancing-language-model-reasoning/)
20. **[A Survey on Large Language Models for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-survey-large-language-models-mathematical/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Peng-Yuan Wang, Tian-Shuo Liu, Chenyang Wang, et al.*2025 · 26 citations*
21. [**Scaling Test-Time Compute Without Verification or RL is Suboptimal arXiv:2502.12118**Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/setlur-2025-scaling-test-time-compute-verification/)
22. **[TreeRL: LLM Reinforcement Learning with On-Policy Tree Search](https://md.research.elamur.ai/free/en/papers/hou-2025-treerl-llm-reinforcement-learning-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenyu Hou, Ziniu Hu, Yujiang Li, et al.*2025 · 26 citations*
23. **[START: Self-taught Reasoner with Tools](https://md.research.elamur.ai/free/en/papers/li-2025-start-self-taught-reasoner-tools/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chengpeng Li, Mingfeng Xue, Zhenru Zhang, et al.*2025 · 21 citations*
24. **[REARANK: Reasoning Re-ranking Agent via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhang-2025-rearank-reasoning-re-ranking-agent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Le Zhang, Bo Wang, Xipeng Qiu, et al.*2025 · 12 citations*
25. [**Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation arXiv:2604.13010**Yecheng Wu, Song Han, Han Cai*2026 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wu-2026-lightning-opd-efficient-post-training/)
26. [**Guiding Reasoning in Small Language Models with LLM Assistance arXiv:2504.09923**Yujin Kim, Euiin Yi, Minu Kim, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/kim-2025-guiding-reasoning-small-language-models/)
27. **[Thinking Out Loud: Do Reasoning Models Know When They're Right?](https://md.research.elamur.ai/free/en/papers/zeng-2025-thinking-out-loud-do-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingcheng Zeng, Weihao Xuan, Leyang Cui, et al.*2025 · 9 citations*
28. **[SPPO: Sequence-Level PPO for Long-Horizon Reasoning Tasks](https://md.research.elamur.ai/free/en/papers/wang-2026-sppo-sequence-level-ppo-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyi Wang, Yixia Li, Long Li, et al.*2026 · 8 citations*
29. **[Understanding the Thinking Process of Reasoning Models: A Perspective from Schoenfeld's Episode Theory](https://md.research.elamur.ai/free/en/papers/li-2025-understanding-thinking-process-reasoning-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ming Li, Nan Zhang, Chenrui Fan, et al.*2025 · 6 citations*
30. [**Self-Distilled Policy Gradient arXiv:2606.04036**Yifeng Liu, Shiyuan Zhang, Yifan Zhang, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/liu-2026-self-distilled-policy-gradient/)
31. [**What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT arXiv:2509.19284**Yunzhen Feng, Julia Kempe, Cheng Zhang, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-characterizes-effective-reasoning-revisiting-length/)
32. **[Controllable LLM Reasoning via Sparse Autoencoder-Based Steering](https://md.research.elamur.ai/free/en/papers/fang-2026-controllable-llm-reasoning-sparse-autoencoder/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Fang, Wenjie Wang, Mingfeng Xue, et al.*2026 · 3 citations*
33. **[Coordinates from Context: Using LLMs to Ground Complex Location References](https://md.research.elamur.ai/free/en/papers/masis-2026-coordinates-context-llms-ground-complex/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tessa Masis, Brendan O'Connor*2026 · 1 citation*
34. **[Inferring Events from Time Series using Language Models](https://md.research.elamur.ai/free/en/papers/tan-2026-inferring-events-time-series-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingtian Tan, Mike A Merrill, Zachary Gottesman, et al.*2026 · 1 citation*
35. **[ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments](https://md.research.elamur.ai/free/en/papers/wang-2026-reasoningguard-safeguarding-large-reasoning-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuquan Wang, Mi Zhang, Yining Wang, et al.*2026 · 1 citation*
36. **[Thinking Long, but Short: Stable Sequential Test-Time Scaling for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/metel-2026-thinking-long-but-short-stable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michael R. Metel, Yufei Cui, Boxing Chen, et al.*2026 · 1 citation*
37. [**Language Specific Knowledge: Do Models Know Better in X than in English? arXiv:2505.14990**Ishika Agarwal, Nimet Beyza Bozdag, Dilek Hakkani-Tur*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/agarwal-2025-language-specific-knowledge-models-know/)
38. **[AdapThink: Adaptive Thinking Preferences for Reasoning Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-adapthink-adaptive-thinking-preferences-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenyue Xu, Xu Wan, Wei Wang, et al.*2026*
39. **[Beyond Simple Term Injection: Reasoning Models for Legal Translation in a Non-Dominant Language Variety](https://md.research.elamur.ai/free/en/papers/natale-2026-beyond-simple-term-injection-reasoning/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Paolo Di Natale, Elena Chiocchetti, Marlies Alber, et al.*2026*
40. **[Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/wang-2026-enhancing-llm-based-search-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junzhe Wang, Zhiheng Xi, Yajie Yang, et al.*2026*
41. **[Exploiting Tree Structure for Credit Assignment in Reinforcement Learning with Large Language Models](https://md.research.elamur.ai/free/en/papers/tran-2026-exploiting-tree-structure-credit-assignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hieu Tran, Zonghai Yao, Hong yu*2026*
42. **[Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement](https://md.research.elamur.ai/free/en/papers/sun-2026-learning-cognition-enhancing-rl-efficiency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zexu Sun, Yongcheng Zeng, Erxue Min, et al.*2026*
43. **[RiT: Rubrics-in-Thinking Reinforcement Learning for Improved Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/tian-2026-rit-rubrics-thinking-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaobin Tian, Shuai Yuan, Muyun Ding, et al.*2026*

65 more citing papers of our library have no page here yet.

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