Juno: Taming Predictive Latents for Vision-Language-Action M
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Source roundup from published reports. Claims below are attributed to their publishers, not independently verified. arXiv Robotics — research abstracts: Juno: Taming Predictive Latents for Vision-Language-Action Models. Juno is a unified framework for vision-language-action (VLA) models that addresses three key failures in predictive latent representation: embodiment-specific control mismatch, action learning interference, and teacher m…
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- arXiv Robotics — research abstractsJuno: Taming Predictive Latents for Vision-Language-Action Models
Juno is a unified framework for vision-language-action (VLA) models that addresses three key failures in predictive latent representation: embodiment-specific control mismatch, action learning interference, and teacher miscalibration under distribution shifts. It improves success rates in both simulated and real-world environments, achieving 72.7% on SimplerEnv and retaining 70–75% success under various shifts on real robots.
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