Papers with end-to-end VLN model

1 papers
MapNav: A Novel Memory Representation via Annotated Semantic Maps for VLM-based Vision-and-Language Navigation (2025.acl-long)

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Challenge: Vision-language navigation (VLN) is a key task in Embodied AI . traditional approaches rely on historical observations as spatio-temporal contexts for decision making .
Approach: They propose a vision-language navigation model that leverages an annotation system to replace historical frames.
Outcome: The proposed model can be used as a new memory representation method in vision-language navigation . it can be applied to simulated and real-world environments, and it is validated by experiments .

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