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Video-HolmesV2: Can MLLMs Reason with Spatio-Temporal Audio-Visual Evidence in Long Videos?

Paper recorded by Signals 4 on 2026-09-15 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16

Category: cs.CV · 计算机视觉 · first seen 2026-09-16

Abstract

Multimodal Large Language Models have demonstrated impressive video understanding, yet their ability to reason over long-form narratives is often masked by visual-centric evaluations and inefficient context processing. Existing benchmarks over-rely on visual heuristics while marginalizing auditory cues, effectively reducing models to "silent observers" that bypass genuine cross-modal reasoning. Mo

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#38 most recent of 237 cs.CV papers we have recorded · ↑ newer: Exploring 2D backbone effects for indoor semantic occupancy prediction · ↓ older: DecoGS: Adaptive Static-Dynamic Decoupling of 3D Gaussians for Free-Vi
Cite this page: Video-HolmesV2: Can MLLMs Reason with Spatio-Temporal Audio-Visual Evidence in Long Videos?: the #38 most recent of 237 cs.CV papers we have recorded (as of 2026-09-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/video-holmesv2-can-mllms-reason-with-spatio-temporal-audio-visual-evidence-in-lo.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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