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Breaking the Vision-Action Shortcut: Latent Interface Training for Generalizable Robotics Foundation Models

62 upvotes · 11 SEP 2026 · Jianman Lin, Shailesh Shailesh, Zhongyi Luo et al.

This paper proposes a method called Latent Interface Training (LIT) to improve the generalization of robotics foundation models by preventing them from relying on visual shortcuts when learning to generate actions from pre-trained visual representations. This is important for robots to perform well in new, unseen environments.

continual learningroboticsvision-action modelslatent interfacesaction generationvisual conditioning