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Current models falter in executing cross-modal editing instructions, revealing significant gaps in audio-visual consistency and fidelity.
Current video editing models falter under the weight of complex user instructions, often omitting critical edits and introducing artifacts.
Span-level error localization can boost deep-research agent reliability by up to 30 percentage points, revealing critical insights into where agents go wrong.
