RIPT-VLA applies RL with dynamic rollout sampling and leave-one-out advantage estimation to fine-tune VLA models, achieving up to 97.5% success rates and recovering from 4% to 97% success with one demonstration in 15 iterations.
Sanketi, Grecia Salazar, Michael S
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Interactive Post-Training for Vision-Language-Action Models
RIPT-VLA applies RL with dynamic rollout sampling and leave-one-out advantage estimation to fine-tune VLA models, achieving up to 97.5% success rates and recovering from 4% to 97% success with one demonstration in 15 iterations.