--- title: "Who cites Reinforcement Learning with — 62 citing papers" description: "62 papers of the Elamur Research library cite «Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in…" canonical: "https://research.elamur.ai/free/en/papers/wen-2025-reinforcement-learning-verifiable-rewards-implicitly/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wen-2025-reinforcement-learning-verifiable-rewards-implicitly/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Reinforcement Learning with Verifiable Rewards…](https://md.research.elamur.ai/free/en/papers/wen-2025-reinforcement-learning-verifiable-rewards-implicitly/) / cited by # Who cites «Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs» 62 papers of our library cite it (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · [← back to «Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs»](https://md.research.elamur.ai/free/en/papers/wen-2025-reinforcement-learning-verifiable-rewards-implicitly/) 1. **[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* 2. **[OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment](https://md.research.elamur.ai/free/en/papers/liu-2026-openrubrics-scalable-synthetic-rubric-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianci Liu, Ran Xu, Tony Yu, et al.*2026 · 25 citations* 3. [**Rethinking Rubric Generation for Improving LLM Judge and Reward Modeling for Open-ended Tasks arXiv:2602.05125**William F. Shen, Xinchi Qiu, Chenxi Whitehouse, et al.*2026 · 9 citations*](https://md.research.elamur.ai/free/en/papers/shen-2026-rethinking-rubric-generation-improving-llm/) 4. [**HunyuanOCR Technical Report arXiv:2511.19575**Hunyuan Vision Team, Pengyuan Lyu, Xingyu Wan, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-vision-hunyuanocr-technical-report/) 5. **[Thinking beyond the anthropomorphic paradigm benefits LLM research](https://md.research.elamur.ai/free/en/papers/ibrahim-2026-thinking-beyond-anthropomorphic-paradigm-benefits/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lujain Ibrahim, Myra Cheng*2026 · 8 citations* 6. **[Beyond Majority Voting: Towards Fine-grained and More Reliable Reward Signal for Test-Time Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-beyond-majority-voting-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiqin Wang, Yile Wang, Kehao Chen, et al.*2026 · 4 citations* 7. **[No More Stale Feedback: Co-Evolving Critics for Open-World Agent Learning](https://md.research.elamur.ai/free/en/papers/li-2026-no-more-stale-feedback-co/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhicong Li, Lingjie Jiang, Yulan Hu, et al.*2026 · 3 citations* 8. **[Beyond Outcome Verification: Verifiable Process Reward Models for Structured Reasoning](https://md.research.elamur.ai/free/en/papers/pronesti-2026-beyond-outcome-verification-verifiable-process/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Massimiliano Pronesti, Anya Belz, Yufang Hou*2026 · 2 citations* 9. **[A Comprehensive Evaluation of Chain-of-Thought Faithfulness in Persian Classification Tasks](https://md.research.elamur.ai/free/en/papers/yazdani-2026-comprehensive-evaluation-chain-thought-faithfulness/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Shakib Yazdani, Cristina España-Bonet, Eleftherios Avramidis, et al.*2026 · 1 citation* 10. **[AT\texttwosuperiorPO: Agentic Turn-based Policy Optimization via Tree Search](https://md.research.elamur.ai/free/en/papers/zong-2026-texttwosuperiorpo-agentic-turn-based-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zefang Zong, Dingwei Chen, Yang Li, et al.*2026* 11. **[Evo-PI: Aligning Medical Reasoning via Evolving Principle-Guided Supervision](https://md.research.elamur.ai/free/en/papers/zheng-2026-evo-pi-aligning-medical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianda Zheng, Huan Gao, Meng-Fen Chiang, et al.*2026* 12. **[MDP-GRPO: Stabilized Group Relative Policy Optimization for Multi-Constraint Instruction Following](https://md.research.elamur.ai/free/en/papers/zarchi-2026-mdp-grpo-stabilized-group-relative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Mahdi Salmani-Zarchi, Zahra Rahimi, Heshaam Faili, et al.*2026* 13. **[Reward Modeling for Scientific Writing Evaluation](https://md.research.elamur.ai/free/en/papers/sahinuc-2026-reward-modeling-scientific-writing-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Furkan Şahinuç, Subhabrata Dutta, Iryna Gurevych*2026* 14. **[ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-scalebox-enabling-high-fidelity-scalable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiasheng Zheng, Xin Zheng, Boxi Cao, et al.*2026* 15. **[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* 16. **[Tandem Training for Language Models](https://md.research.elamur.ai/free/en/papers/west-2026-tandem-training-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Robert West, Ashton Anderson, Ece Kamar, et al.*2026* 17. **[The Inner Monologue of Language Models: When Reasoning Traces Reveal More Than They Hide](https://md.research.elamur.ai/free/en/papers/singla-2026-inner-monologue-language-models-when/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pratham Singla, Shivank Garg, Ayush Singh, et al.*2026* 45 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wen-2025-reinforcement-learning-verifiable-rewards-implicitly/) — Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs