---
title: "Who cites MiMo-Audio: Audio Language — 22 citing papers"
description: "22 papers of the Elamur Research library cite «MiMo-Audio: Audio Language Models are Few-Shot Learners», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [MiMo-Audio: Audio Language Models are Few-Shot…](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/) / cited by

# Who cites «MiMo-Audio: Audio Language Models are Few-Shot Learners»

22 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 «MiMo-Audio: Audio Language Models are Few-Shot Learners»](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/)

1. [**Qwen3.5-Omni Technical Report arXiv:2604.15804**Qwen Team*2026 · 29 citations*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-5-omni-technical/)
2. [**Qwen3-TTS Technical Report arXiv:2601.15621**Hangrui Hu, Xinfa Zhu, Ting He, et al.*2026 · 14 citations*](https://md.research.elamur.ai/free/en/papers/hu-2026-qwen3-tts-technical-report/)
3. **[Closing the Modality Reasoning Gap for Speech Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-closing-modality-reasoning-gap-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoren Wang, Heng Lu, Xueyao Zhang, et al.*2026 · 2 citations*
4. **[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*
5. **[UniSRM: A Unified Speech Reward Model for Reasoning-Based Fine-grained Assessment](https://md.research.elamur.ai/free/en/papers/wang-2026-unisrm-unified-speech-reward-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanyuan Wang, Dongchao Yang, Yayue Deng, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/) — MiMo-Audio: Audio Language Models are Few-Shot Learners