EChO-Agent: Evidence Chain Orchestration Agent for Audio Reasoning

Siyuan Zhang; Jian Zong; Junyu Wang; Peiyuan Jiang; Jiahao Yan; Jingyu Zhang; Tianrui Wang; Xiaobao Wang; Longbiao Wang; Jianwu Dang

arXiv · 2606.15141

EChO-Agent: Evidence Chain Orchestration Agent for Audio Reasoning

Siyuan Zhang·Jian Zong·Junyu Wang·Peiyuan Jiang·Jiahao Yan·Jingyu Zhang·Tianrui Wang·Xiaobao Wang·Longbiao Wang·Jianwu Dang

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Abstract

While LALMs show promise on audio question answering, they fail to focus on question-relevant segments of audio and provide a clear, checkable reasoning process when dealing with complex audio reasoning. Reinforcement learning and tool-augmented prompting can help models better relate questions to audio but lack a reliable way to understand, integrate, and self-verify audio segments. To address this gap, we present EChO-Agent, a modular agent framework that reformulates complex audio QA as a planning, tool execution, evidence integration, and answer verification workflow. Experiments on MMAR benchmark show EChO-Agent improves both accuracy and rubric scores over baseline and ablation studies show evidence integration is the key factor.

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BibTeX RIS

Siyuan Zhang, Jian Zong, Junyu Wang, Peiyuan Jiang, Jiahao Yan, Jingyu Zhang, Tianrui Wang, Xiaobao Wang, Longbiao Wang, Jianwu Dang. 2026-06-13. EChO-Agent: Evidence Chain Orchestration Agent for Audio Reasoning. https://arxiv.org/abs/2606.15141

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