VLN-Cache delivers up to 1.52x faster inference in VLN models by using view-aligned remapping for geometric consistency and a task-relevance saliency filter to manage semantic changes during navigation.
Openvla: An open-source vision-language-action model
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Vision-language models generate executable Behavior Tree policies for robots from synthetic vision-language data, with successful transfer demonstrated on two real manipulators.
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VLN-Cache: Enabling Token Caching for VLN Models with Visual/Semantic Dynamics Awareness
VLN-Cache delivers up to 1.52x faster inference in VLN models by using view-aligned remapping for geometric consistency and a task-relevance saliency filter to manage semantic changes during navigation.
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Learning Structured Robot Policies from Vision-Language Models via Synthetic Neuro-Symbolic Supervision
Vision-language models generate executable Behavior Tree policies for robots from synthetic vision-language data, with successful transfer demonstrated on two real manipulators.