LingBot-VLA 2.0: Built for Robot Control
bendee983 · x · 2026-07-11
To address the high latency and lack of action cognition when directly adapting video models for robotics, LingBot-VLA 2.0 is trained from scratch specifically for robot control.
Its core architecture features a visual tokenizer, action prediction, and a full causal Transformer. The model leverages web-scale video (including human demonstrations) for scalable self-supervised learning to capture action-relevant visual dynamics.
Evaluation Performance:
- Rapidly adapts with only 10-15 demonstrations
- Supports transfer across different robot embodiments
- Achieves a 93.6% score on the RoboTwin 2.0 benchmark
Related event: LingBot-VA/VLA 2.0 Released: Native Embodied Foundation Model(24 posts)→
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