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Vision-language-action models let robots follow language instructions, but their language backbones of several billion parameters are the main obstacle to running them on robot hardware, and removing 63% of it from OpenVLA-OFT drops LIBERO-Long success from 93.2% to 0.8%.
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.