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This visually grounded, multi-probe evaluation first verifies that a model recognizes each concept from the image, then tests its recoverability through multiple-choice, short-answer, and indirect queries.
A benchmark that tests the ability of agentic video understanding by asking agents to reconstruct real-world videos as animated Blender scenes, and shows that programmatic reconstruction is a viable test of agentic video understanding, and that semantic retention remains the main challenge.
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