🔗 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»

1. Qwen3.5-Omni Technical ReportarXiv:2604.15804Qwen Team2026 · 29 citations
2. Qwen3-TTS Technical ReportarXiv:2601.15621Hangrui Hu, Xinfa Zhu, Ting He, et al.2026 · 14 citations
3. Closing the Modality Reasoning Gap for Speech Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (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 UnderstandingFindings of the Association for Computational LinguisticsQuanwei Tang, Dong Zhang, Shoushan Li, et al.2026
5. UniSRM: A Unified Speech Reward Model for Reasoning-Based Fine-grained AssessmentAnnual Meeting of the Association for Computational Linguistics (ACL)Yuanyuan Wang, Dongchao Yang, Yayue Deng, et al.2026

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

This page in Markdown → https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/cited-by/