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GuidedNav: Shaping Vision-Language Navigation Representations through Pre-action Attention and Spatial Guidance

GuidedNav shapes vision-language navigation representations during training with subtask, landmark, and spatial guidance. It aligns pre-action attention with the active instruction segment and relevant visual regions, then distills long-horizon geometry and local spatial structure into a monocular RGB policy. The method improves success rates on R2R-CE and RxR-CE val-unseen while avoiding intermediate textual reasoning and online geometric encoding at inference.