arXiv Machine Learning July 24, 2026 By Dongjie Fu, Di Cao, Xize Cheng, Zihan Zhang, Wenxu Jia, Yifu Chen, Shengpeng Ji, Yu Zhang, Tao Jin

X$^3$-OPD: Distilling Reasoning into Large Audio-Language Models via On-Policy Alignment

Read the original on arXiv Machine Learning →

arXiv:2607. 21550v1 Announce Type: new Abstract: While large audio-language models have achieved remarkable progress in auditory perception, they still lag behind text-based large language models in deep logical reasoning, primarily due to the scarcity of high-quality audio reasoning data.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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AudioDER: A Deduplication-Enhanced Reasoning Dataset for Post-Training Large Audio-Language Models

Listen Then Reason: Perception-Grounded Test-Time Reinforcement Learning for Large Audio-Language Models

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