---
title: "Who cites Self-Evolving Curriculum for LLM Reasoning"
description: "20 papers of the Elamur Research library cite «Self-Evolving Curriculum for LLM Reasoning», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/chen-2025-self-evolving-curriculum-llm-reasoning/cited-by/"
---
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# Who cites «Self-Evolving Curriculum for LLM Reasoning»

20 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «Self-Evolving Curriculum for LLM Reasoning»](https://md.research.elamur.ai/free/en/papers/chen-2025-self-evolving-curriculum-llm-reasoning/)

1. [**Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning arXiv:2506.06632**Shubham Parashar, Shurui Gui, Xiner Li, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/parashar-2025-curriculum-reinforcement-learning-easy-hard/)
2. **[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*
3. **[What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/jia-2026-what-makes-good-curriculum-disentangling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaning Jia, Chunhui Zhang, Xingjian Diao, et al.*2026 · 4 citations*
4. **[Imbalanced Gradients in RL Post-Training of Multi-Task LLMs](https://md.research.elamur.ai/free/en/papers/wu-2026-imbalanced-gradients-rl-post-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Runzhe Wu, Ankur Samanta, Ayush Jain, et al.*2026 · 3 citations*
5. **[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*
6. **[SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data Utility](https://md.research.elamur.ai/free/en/papers/zhi-2026-spard-self-paced-curriculum-rl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuyang Zhi, Peilun Zhou, Chengqiang Lu, et al.*2026 · 1 citation*
7. **[Balancing Knowledge Breadth and Task Depth for Effective Domain Adaptation Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-balancing-knowledge-breadth-task-depth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mu Zhang, Yuxiang Chu, Guangya Yu, et al.*2026*
8. **[DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections](https://md.research.elamur.ai/free/en/papers/shin-2026-dynamixsft-dynamic-mixture-optimization-instruction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haebin Shin, Lei Ji, Xiao Liu, et al.*2026*

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

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