Efficient Agentic Audio-Visual Question Answering through Toolset Pruning and Modality Consolidation
arXiv:2610.38960v1 Announce Type: new Abstract: Fine-grained audio-visual question answering (AVQA) requires models to resolve complex cross-modal correspondences and temporally grounding from sparsely distributed evidence. Omni-modal agents, which autonomously orchestrate perception tools to actively collect evidence, achieve strong performance, but it remains unclear whether active perception from both audio and visual modalities depends on broad specialized toolsets, especially audio or visu…