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CoTinyVLA outperforms larger models by 15.9 points in the most challenging tasks, proving that smarter supervision beats sheer size in VLA systems.
Achieve video outpainting with superior temporal coherence and visual realism by unifying propagation-based and generation-based paradigms.
Unsupervised video object segmentation gets a boost from CMTM, a new method that intelligently mixes appearance and motion cues using transformers and token masking to achieve SOTA results.
