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This work introduces ReShoot, a framework that synthesizes visual diversity by re-rendering previously recorded demonstrations under altered appearances, thereby shifting the burden from data collection to generation.
CoTinyVLA outperforms larger models by 15.9 points in the most challenging tasks, proving that smarter supervision beats sheer size in VLA systems.