X-Fly: Learning to Reach and Stop in Full-Chunk Aerial Vision-Language Navigation
Aerial vision-language navigation (VLN) agents built on large vision-language models are expensive to query. Executing a complete predicted action chunk before replanning amortizes this cost, reducing model inference from 195 to 42 ms per executed waypoint for our policy. It also moves the states at which the policy is...
Rui-Bin Ju, Rui Cai, Min Xu et al.
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