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Pretraining loss actively misleads video data curation: broad data coverage systematically beats aggressive quality filtering across downstream benchmarks in both Wan 2.1 and V-JEPA 2.1.
Retaining critical information in robot locomotion can yield a 15% performance boost while simplifying the model's architecture.
AnchorScore reveals a reliable method to identify which classes MLLMs struggle to annotate, potentially saving researchers significant time and resources in evaluation.
