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Current MLLMs falter in following complex video instructions, revealing a significant oversight in their evaluation metrics.
FIRM-Video reveals that a checklist-driven approach can significantly enhance the reliability of text-to-video reward modeling, achieving state-of-the-art performance in evaluation metrics.