---
title: "Who cites REINFORCE++: Stabilizing — 102 citing papers"
description: "102 papers of the Elamur Research library cite «REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage…"
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---
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# Who cites «REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization»

102 papers of our library cite it (of the 149,439 whose bibliographies we read) · 42 with a page here, the most cited first · [← back to «REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization»](https://md.research.elamur.ai/free/en/papers/hu-2025-reinforce-stabilizing-critic-free-policy/)

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. [**Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paper**Yang Yue, Zhiqi Chen, Rui Lu, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-reinforcement-learning-really-incentivize-reasoning/)
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. [**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/)
5. [**Demystifying Long Chain-of-Thought Reasoning in LLMs arXiv:2502.03373**Edward Yeo, Yuxuan Tong, Morry Niu, et al.*2025 · 119 citations*](https://md.research.elamur.ai/free/en/papers/yeo-2025-demystifying-long-chain-thought-reasoning/)
6. [**The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models arXiv:2505.22617**Ganqu Cui, Yuchen Zhang, Jiacheng Chen, et al.*2025 · 101 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-entropy-mechanism-reinforcement-learning-reasoning/)
7. **[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*
8. [**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/)
9. [**VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks arXiv:2504.05118**Yu Yue, Yufeng Yuan, Qiying Yu, et al.*2025 · 68 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-vapo-efficient-reliable-reinforcement-learning/)
10. **[Absolute Zero: Reinforced Self-play Reasoning with Zero Data](https://md.research.elamur.ai/free/en/papers/zhao-2025-absolute-zero-reinforced-self-play/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Andrew Zhao, Yiran Wu, Yang Yue, et al.*2025 · 57 citations*
11. **[Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/bae-2026-online-difficulty-filtering-reasoning-oriented/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sanghwan Bae, Jiwoo Hong, Min Young Lee, et al.*2026 · 22 citations*
12. **[Rethinking Entropy Interventions in RLVR: An Entropy Change Perspective](https://md.research.elamur.ai/free/en/papers/hao-2026-rethinking-entropy-interventions-rlvr-entropy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhezheng Hao, Hong Wang, Haoyang Liu, et al.*2026 · 22 citations*
13. **[Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2025-search-refine-during-think-facilitating/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yaorui Shi, Sihang Li, Chang Wu, et al.*2025 · 18 citations*
14. **[DeepTrans: Deep Reasoning Translation via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-deeptrans-deep-reasoning-translation-reinforcement/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaan Wang, Fandong Meng, Jie Zhou*2026 · 11 citations*
15. **[Optimizing Length Compression in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/cheng-2026-optimizing-length-compression-large-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxiang Cheng, Dongping Chen, Mingyang Fu, et al.*2026 · 11 citations*
16. **[Step Potential Advantage Estimation: Harnessing Intermediate Confidence and Correctness for Efficient Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-step-potential-advantage-estimation-harnessing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fei Wu, Zhenrong Zhang, Qikai Chang, et al.*2026 · 11 citations*
17. **[SoundMind: RL-Incentivized Logic Reasoning for Audio-Language Models](https://md.research.elamur.ai/free/en/papers/diao-2025-soundmind-rl-incentivized-logic-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xingjian Diao, Chunhui Zhang, Keyi Kong, et al.*2025 · 11 citations*
18. [**QwenLong-L1.5: Post-Training Recipe for Long-Context Reasoning and Memory Management arXiv:2512.12967**Weizhou Shen, Ziyi Yang, Chenliang Li, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-qwenlong-l1-5-post/)
19. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
20. **[Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments](https://md.research.elamur.ai/free/en/papers/ye-2026-feedback-driven-tool-use-improvements/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junjie Ye, Changhao Jiang, Zhengyin Du, et al.*2026 · 6 citations*
21. **[EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis](https://md.research.elamur.ai/free/en/papers/song-2026-envscaler-scaling-tool-interactive-environments/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoshuai Song, Haofei Chang, Guanting Dong, et al.*2026 · 5 citations*
22. **[KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality](https://md.research.elamur.ai/free/en/papers/ren-2026-knowrl-exploring-knowledgeable-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Baochang Ren, Shuofei Qiao, Ningyu Zhang, et al.*2026 · 5 citations*
23. **[Dynamic Sampling that Adapts: Self-Aware Iterative Data Persistent Optimization for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/rao-2026-dynamic-sampling-that-adapts-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jun Rao, Xuebo Liu, Hexuan Deng, et al.*2026 · 4 citations*
24. **[SCALER: Synthetic Scalable Adaptive Learning Environment for Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-scaler-synthetic-scalable-adaptive-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Caijun Xu, Changyi Xiao, Zhongyuan Peng, et al.*2026 · 2 citations*
25. **[Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-not-all-tokens-matter-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanbing Liu, Lang Cao, Yuanyi Ren, et al.*2026 · 1 citation*
26. **[A Survey of Large Language Model-Based Search Agents](https://md.research.elamur.ai/free/en/papers/xi-2026-survey-large-language-model-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunjia Xi, Jianghao Lin, Yongzhao Xiao, et al.*2026*
27. **[AAPO: Enhancing the Reasoning Capabilities of LLMs with Advantage Margin](https://md.research.elamur.ai/free/en/papers/xiong-2026-aapo-enhancing-reasoning-capabilities-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jian Xiong, Jingbo Zhou, Jingyong Ye, et al.*2026*
28. **[AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/sun-2026-agentgl-agentic-graph-learning-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanfu Sun, Kang Li, Dongzhe Fan, et al.*2026*
29. **[Can Small LLMs Learn a Robust Theory of Mind via RLVR? Investigating Generalization through the False-Belief Task](https://md.research.elamur.ai/free/en/papers/sarangi-2026-can-small-llms-learn-robust/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sneheel Sarangi, Hanan Salam*2026*
30. **[Crossing the Reward Bridge: Expanding Reinforcement Learning with Verifiable Rewards Across Diverse Domains](https://md.research.elamur.ai/free/en/papers/su-2026-crossing-reward-bridge-expanding-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Su, Dian Yu, Linfeng Song, et al.*2026*
31. **[Don't Tell the Answer, Truly Guide the Reasoning During RL Rollouts](https://md.research.elamur.ai/free/en/papers/wang-2026-don-t-tell-answer-truly/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyi Wang, Jinyi Han, Zishang Jiang, et al.*2026*
32. **[Efficient KL Divergence Estimation via Truncated Top-K Integration for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-efficient-kl-divergence-estimation-truncated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyuan Wang, Luozhijie Jin, Bo Wang, et al.*2026*
33. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-generalizable-llm-learning-graph-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizhuo Zhang, Heng Wang, Shangbin Feng, et al.*2026*
34. **[Joint Optimization of Training Data and Policy in RLHF](https://md.research.elamur.ai/free/en/papers/yu-2026-joint-optimization-training-data-policy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuohao Yu, Jiali Zeng, Weizheng Gu, et al.*2026*
35. **[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*
36. **[MemCoRL: Alternating Co-Optimization of Memory Retrieval and Utilization via Collaborative Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-memcorl-alternating-co-optimization-memory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuewen Liu, Peng Xu, Muxi Diao, et al.*2026*
37. **[RepoDistill: Distilling Repository Knowledge through Compression-Aware Budget Allocation and Policy Optimization](https://md.research.elamur.ai/free/en/papers/yin-2026-repodistill-distilling-repository-knowledge-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin Yin, Zixiang Ding, Yiang Zhang, et al.*2026*
38. **[Revisiting Entropy Regularization: Adaptive Coefficient Unlocks Its Potential for LLM Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhang-2026-revisiting-entropy-regularization-adaptive-coefficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoyun Zhang, Xiaojian Yuan, Di Huang, et al.*2026*
39. **[STCOR: A Trilevel Syllogism-Driven Reasoning Framework](https://md.research.elamur.ai/free/en/papers/yang-2026-stcor-trilevel-syllogism-driven-reasoning/) [Workshop on Argument Mining](https://md.research.elamur.ai/free/en/venues/argmining/)**Keying Yang, Hao Wang, Chengtao Jian, et al.*2026*
40. **[Tailored Primitive Initialization is the Secret Key to Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yao-2026-tailored-primitive-initialization-is-secret/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihang Yao, Guangtao Zeng, Raina Wu, et al.*2026*
41. **[The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAG](https://md.research.elamur.ai/free/en/papers/zhou-2026-retrieval-bottleneck-scaling-laws-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shu Zhou, Jinman Leng, Yufei Song, et al.*2026*
42. **[TRAC: Teacher-Guided Token Reward with Adaptive Calibration for Robust Policy Optimization](https://md.research.elamur.ai/free/en/papers/wu-2026-trac-teacher-guided-token-reward/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sitong Wu, Haoru Tan, Xichen Zhang, et al.*2026*

60 more papers of our library cite it; they have no page here yet.

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