Past-Token Prediction, an auxiliary loss that makes diffusion policies predict past action tokens, improves long-context imitation learning success roughly 3x over baselines while a cached-embedding recipe cuts training cost.
RT-1: Robotics Transformer for Real-World Control at Scale
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Learning Long-Context Diffusion Policies via Past-Token Prediction
Past-Token Prediction, an auxiliary loss that makes diffusion policies predict past action tokens, improves long-context imitation learning success roughly 3x over baselines while a cached-embedding recipe cuts training cost.