---
title: "Who cites Can Large Reasoning Models — 16 citing papers"
description: "16 papers of the Elamur Research library cite «Can Large Reasoning Models Self-Train?», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/shafayat-2025-large-reasoning-models-self-train/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Can Large Reasoning Models Self-Train?](https://md.research.elamur.ai/free/en/papers/shafayat-2025-large-reasoning-models-self-train/) / cited by

# Who cites «Can Large Reasoning Models Self-Train?»

16 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «Can Large Reasoning Models Self-Train?»](https://md.research.elamur.ai/free/en/papers/shafayat-2025-large-reasoning-models-self-train/)

1. [**Spurious Rewards: Rethinking Training Signals in RLVR arXiv:2506.10947**Rulin Shao, Shuyue Stella Li, Rui Xin, et al.*2025 · 53 citations*](https://md.research.elamur.ai/free/en/papers/shao-2025-spurious-rewards-rethinking-training-signals/)
2. [**Learning to Reason without External Rewards arXiv:2505.19590**Xuandong Zhao, Zhewei Kang, Aosong Feng, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-learning-reason-external-rewards/)
3. [**A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence arXiv:2507.21046**Huan-ang Gao, Jiayi Geng, Wenyue Hua, et al.*2025 · 36 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-survey-self-evolving-agents-where/)
4. [**Outcome-based Exploration for LLM Reasoning arXiv:2509.06941**Yuda Song, Julia Kempe, Remi Munos*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-outcome-based-exploration-llm-reasoning/)
5. **[What If Consensus Lies? Selective-Complementary Reinforcement Learning at Test Time](https://md.research.elamur.ai/free/en/papers/yan-2026-what-if-consensus-lies-selective/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dong Yan, Jian Liang, Yanbo Wang, et al.*2026 · 2 citations*
6. **[CoAct: Co-Active LLM Preference Learning with Human-AI Synergy](https://md.research.elamur.ai/free/en/papers/xu-2026-coact-co-active-llm-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.*2026 · 1 citation*
7. **[Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2026-easy-samples-are-all-you/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiyin Yu, Bo Zhang, Qibin Hou, et al.*2026 · 1 citation*
8. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026*
9. **[Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward](https://md.research.elamur.ai/free/en/papers/wen-2026-verifier-free-rl-llms-intrinsic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuexiang Wen, Hang Yu, Linchao Zhu, et al.*2026*

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

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