R&B-EnCoRe: Self-Supervised Pre-Training for VLA Models to Discover Effective Reasoning Steps
dl_weekly · x · 2026-07-04
R&B-EnCoRe is a newly proposed self-supervised pre-training recurrent method designed specifically for Vision-Language-Action (VLA) models. Unlike traditional fixed templates, this framework allows the model to autonomously explore and discover which reasoning steps actually improve action prediction, rather than passively following a preset reasoning chain.
By utilizing self-supervised signals for pre-training, this method promises to enhance the generalization and reasoning quality of robotic control models, marking an exploratory advancement in VLA training paradigms.
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