---
title: "Who cites Audio-Reasoner: Improving — 16 citing papers"
description: "16 papers of the Elamur Research library cite «Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/zhifei-2025-audio-reasoner-improving-reasoning-capability/cited-by/"
---
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# Who cites «Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models»

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 «Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models»](https://md.research.elamur.ai/free/en/papers/zhifei-2025-audio-reasoner-improving-reasoning-capability/)

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. **[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*
3. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
4. **[Listen, Pause, and Reason: Toward Perception-Grounded Hybrid Reasoning for Audio Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-listen-pause-reason-perception-grounded/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jieyi Wang, Yazhe Niu, Dexuan Xu, et al.*2026 · 1 citation*
5. **[Don't Just Listen, Try Planning: Graph-based Retrieval-Generation Agent for Long-form Audio Meeting Understanding](https://md.research.elamur.ai/free/en/papers/tang-2026-don-t-just-listen-try/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Quanwei Tang, Dong Zhang, Shoushan Li, et al.*2026*
6. **[ORCA: Open-ended Response Correctness Assessment for Audio Question Answering](https://md.research.elamur.ai/free/en/papers/sedlacek-2026-orca-open-ended-response-correctness/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Šimon Sedláček, Sara Barahona, Cecilia Bolaños, et al.*2026*
7. **[RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios](https://md.research.elamur.ai/free/en/papers/zhang-2026-rsa-bench-benchmarking-audio-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Zhang, Kaiwen Luo, Liang Lin, et al.*2026*
8. **[SDiaReward: Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness](https://md.research.elamur.ai/free/en/papers/lu-2026-sdiareward-modeling-benchmarking-spoken-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyu Lu, Yuhan Wang, Fan Zhuo, et al.*2026*
9. **[Think Smart, Not Hard: Difficulty Adaptive Reasoning for Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/sheng-2026-think-smart-not-hard-difficulty/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichao Sheng, Shilin Zhou, Chen Gong, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/zhifei-2025-audio-reasoner-improving-reasoning-capability/) — Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models