---
title: "Who cites Improving Reasoning Capabilities — 9 citing papers"
description: "9 papers of the Elamur Research library cite «Improving Reasoning Capabilities in Small Models through Mixture-of-layers Distillation with…"
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---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/chen-2025-improving-reasoning-capabilities-small-models/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Improving Reasoning Capabilities in Small Models…](https://md.research.elamur.ai/free/en/papers/chen-2025-improving-reasoning-capabilities-small-models/) / cited by

# Who cites «Improving Reasoning Capabilities in Small Models through Mixture-of-layers Distillation with Stepwise Attention on Key Information»

9 papers of our library cite it (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · [← back to «Improving Reasoning Capabilities in Small Models through Mixture-of-layers Distillation with Stepwise Attention on Key Information»](https://md.research.elamur.ai/free/en/papers/chen-2025-improving-reasoning-capabilities-small-models/)

1. **[Logical Phase Transitions: Understanding Collapse in LLM Logical Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2026-logical-phase-transitions-understanding-collapse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinglang Zhang, Yunyao Zhang, ZeLiang Chen, et al.*2026 · 17 citations*
2. **[STRIDE-ED: A Strategy-Grounded Stepwise Reasoning Framework for Empathetic Dialogue Systems](https://md.research.elamur.ai/free/en/papers/ji-2026-stride-ed-strategy-grounded-stepwise/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongru Ji, Yuyin Fan, Meng Zhao, et al.*2026 · 10 citations*
3. **[PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-perm-psychology-grounded-empathetic-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chengbing Wang, Wuqiang Zheng, Yang Zhang, et al.*2026 · 8 citations*
4. **[Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty](https://md.research.elamur.ai/free/en/papers/xue-2026-reason-only-when-needed-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 8 citations*
5. **[Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2026-why-supervised-fine-tuning-fails/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 6 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/chen-2025-improving-reasoning-capabilities-small-models/) — Improving Reasoning Capabilities in Small Models through Mixture-of-layers Distillation with Stepwise Attention on Key Information