---
title: "Who cites Does Math Reasoning Improve — 24 citing papers"
description: "24 papers of the Elamur Research library cite «Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of…"
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# Who cites «Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning»

24 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 «Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning»](https://md.research.elamur.ai/free/en/papers/huan-2025-math-reasoning-improve-general-llm/)

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. [**Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models arXiv:2601.18734**Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.*2026 · 97 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2026-self-distilled-reasoner-policy-self/)
3. [**Self-Distillation Enables Continual Learning arXiv:2601.19897**Idan Shenfeld, Mehul Damani, Jonas Hubotter, et al.*2026 · 62 citations*](https://md.research.elamur.ai/free/en/papers/shenfeld-2026-self-distillation-enables-continual-learning/)
4. [**Front-Loading Reasoning: The Synergy between Pretraining and Post-Training Data arXiv:2510.03264**Syeda Nahida Akter, Shrimai Prabhumoye, Eric Nyberg, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/akter-2025-front-loading-reasoning-synergy-between/)
5. **[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*
6. **[RISER: Orchestrating Latent Reasoning Skills for Adaptive Activation Steering](https://md.research.elamur.ai/free/en/papers/ye-2026-riser-orchestrating-latent-reasoning-skills/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wencheng Ye, Xiaoyang Yuan, Yi Bin, et al.*2026 · 1 citation*
7. **[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*
8. **[Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization](https://md.research.elamur.ai/free/en/papers/xueyun-2026-learning-mistakes-negative-reasoning-samples/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tian Xueyun, MingHua Ma, Bingbing Xu, et al.*2026*
9. **[Why Does Reinforcement Learning Generalize? A Feature-Level Mechanistic Study of Post-Training in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-why-does-reinforcement-learning-generalize/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dan Shi, Zhuowen Han, Simon Ostermann, et al.*2026*

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

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