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Matching papers

PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models

172 upvotes · 14 SEP 2026 · DeepCybo Team, Yu Bin, Haipeng Cao et al.

This paper develops a unified model that can understand physical environments, generate actions, and predict future states, using a combination of vision, language, and embodied interactions. Practitioners may care about this model because it could be used to create robots or other agents that can interact with and adapt to their physical surroundings.

vision-language modelsphysical foundation modelsembodied AImultimodal learningrobotics

Show-Harness: Just a VLM Agent Can Play Robots

89 upvotes · 9 SEP 2026 · Yanzhe Chen, Zechen Bai, Zhijun Cao et al.

This paper shows how a vision-language model (VLM) can control robots without needing extensive pretraining or specialized hardware, by providing a compact interface that links the model's intentions to specific actions. Practitioners might care about this because it could make robots more accessible and user-friendly.

embodied AIvision-language modelsrobot controlsemanticsreinforcement learning