SOURCE-LINKED INTELLIGENCE
Towards Generalizable Visually Grounded Exploration of Household Devices
Recent advancements in Vision-Language Models (VLMs) have demonstrated impressive capabilities in static visual recognition and high-level semantic reasoning. However, current embodied exploration paradigms still heavily rely on imitation learning from human-annotated trajectories, which severely limits agents' generalization ability. The key bottleneck of realizing general autonomous embodied agents lies in Generalizable Visually Grounded Exploration: the ability to operate novel devices without manuals or specific training by actively grounding abstract world knowledge into fine-grained visu
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-01T07:42:45.000Z
First collected: 2026-09-21T06:11:57.537Z. This is not the publication date.