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A novel two-axis framework unifies the study of multimodal agent memory, revealing distinct tiers of memory adaptation from static reuse to self-evolving policies.
Even top-tier VLMs score just 0.632 when reverse-engineering AI video prompts, frequently hallucinating plausible descriptions that completely fail to reproduce the source video's camera and stylistic controls.
CUBIST achieves state-of-the-art results in action quality assessment by leveraging multimodal data for precise error attribution and feedback generation.