OmniDR‑Bench forces multimodal agents to retrieve, locate, and justify audiovisual evidence, exposing a 37 % shortfall in grounded reasoning despite strong answer accuracy [1] . The benchmark’s three‑step rubric—retrieve the right media, pinpoint the supporting segment, then produce a justification—turns “I think so” into “here’s where it happens”.

Before this work, multimodal evaluation largely measured whether a model could name the correct object or answer a question about a video, using metrics such as VQA accuracy or recall‑based retrieval scores. Those benchmarks never required agents to point to a concrete timestamp or cite a supporting clip, leaving an invisible gap between answering and evidencing.

The best of 18 agent configurations reaches only 63.3 out of 100 on OmniDR‑Bench’s evidence metric [1] .…