A VLA that Learns from Experience

What this post added

Introduces Recap (RL with Experience & Corrections via Advantage-conditioned Policies), a method for training robotic models that combines demonstrations, expert corrections, and autonomous experience. Details the use of a value function to predict task progress and an advantage-conditioned policy for learning from experience. Demonstrates improvements in throughput and failure rates for VLA models performing tasks like espresso making, box assembly, and laundry folding.