arXiv 2610.28444 · cs.CV · 2026-10-20
EvaOmni: An Evidence-Grounded Benchmark for Audio-Visual Reasoning
Xiaoxing Hu, Wenxi Yao, Chaoyuan Shi, Ziqi Ye, Xiaorong Guo, Peixuan Li, Zhuoran Sun, Ziyang Gong and 12 more
SJTU VisionXLab
In latest · #304 Added on 2026-10-24
One-line takeaway
SJTU VisionXLab's EvaOmni is an evidence-grounded audio-visual reasoning benchmark that checks whether omni models actually build a reasoning chain from audio and visual evidence, not just answer multiple-choice questions correctly, and guards against text-only or unimodal shortcuts.
上海交大 VisionXLab 的 EvaOmni 是以证据为基础的音视频推理基准：不只看选择题答对没有，还检查模型是否真的从音频和画面证据形成推理链，并防止靠文本或单一模态的捷径答对。
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About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-26.
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