AI RESEARCH
Agentic Active Omni-Modal Perception for Multi-Hop Audio-Visual Reasoning
arXiv CS.AI
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ArXi:2605.28192v1 Announce Type: new Multi-hop audio-visual reasoning remains challenging for Omni-LLMs, as relevant evidence is often sparse, temporally dispersed, and distributed across both audio and visual streams. Existing benchmarks provide limited investigation of this setting, typically involving only a limited number of modalities, relevant temporal segments, or reasoning steps. In this work, we