---
title: "Who cites Superficial Self-Improved — 8 citing papers"
description: "8 papers of the Elamur Research library cite «Superficial Self-Improved Reasoners Benefit from Model Merging», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/yuan-2025-superficial-self-improved-reasoners-benefit/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yuan-2025-superficial-self-improved-reasoners-benefit/cited-by/)

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# Who cites «Superficial Self-Improved Reasoners Benefit from Model Merging»

8 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 «Superficial Self-Improved Reasoners Benefit from Model Merging»](https://md.research.elamur.ai/free/en/papers/yuan-2025-superficial-self-improved-reasoners-benefit/)

1. **[SoundMind: RL-Incentivized Logic Reasoning for Audio-Language Models](https://md.research.elamur.ai/free/en/papers/diao-2025-soundmind-rl-incentivized-logic-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xingjian Diao, Chunhui Zhang, Keyi Kong, et al.*2025 · 11 citations*
2. **[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*
3. **[Behavior Knowledge Merge in Reinforced Agentic Models](https://md.research.elamur.ai/free/en/papers/yuan-2026-behavior-knowledge-merge-reinforced-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangchi Yuan, Dachuan Shi, Chunhui Zhang, et al.*2026 · 3 citations*
4. **[Tailoring Memory Granularity for Multi-Hop Reasoning over Long Contexts](https://md.research.elamur.ai/free/en/papers/qing-2026-tailoring-memory-granularity-multi-hop/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peijun Qing, Xingjian Diao, Chiyu Ma, et al.*2026 · 3 citations*
5. **[What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context](https://md.research.elamur.ai/free/en/papers/ouyang-2026-what-makes-llms-effective-sequential/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyu Ouyang, Qianlong Wen, Chunhui Zhang, et al.*2026 · 1 citation*

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

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