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PASS-VLN: A Passability-Aware Benchmark and Model for Local-Command Vision-and-Language Navigation

PASS-VLN is a passability-aware benchmark and model for local-command vision-and-language navigation (VLN). It holds the scene, instruction, start pose, and reference route fixed while varying only the robot body width, requiring the robot to reach the target when the passage is feasible and to stop early when it is blocked.

Part of the event: PASS-VLN proposes a traversability-aware local navigation benchmark and model

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