SOURCE-LINKED INTELLIGENCE
GroundingVLN: Reasoning and Acting with Grounding for Vision-Language Navigation
Although vision-language models (VLMs) possess strong visual understanding and reasoning capabilities, existing vision-and-language navigation (VLN) agents struggle to connect semantic reasoning with spatial execution. Two coupled gaps remain in this connection, as intermediate reasoning is not explicitly anchored to visual evidence and high-level decisions lack precise spatial goals to guide low-level motion. Cognitive science suggests that human navigation bridges these levels hierarchically by anchoring cognition to relevant landmarks and guiding locomotion toward spatial goals. Motivated b
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T12:41:26.000Z
First collected: 2026-09-20T08:01:03.945Z. This is not the publication date.