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arXiv · 2606.22424

FlowDec: Temporal Conditional Flow Decorruptor for Robust Continuous Vision-Language Navigation

Yufei Zhang·Changhao Chen
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Abstract

Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to follow natural-language instructions in unseen scenes. While Large Models (LMs) have advanced VLN-CE, their performance remains severely degraded by real-world visual corruptions, a critical yet underexplored domain constraint. We introduce Temporal Conditional Flow Decorruptor (FlowDec), a novel image restoration framework tailored for LM-based VLN-CE. FlowDec integrates a hybrid temporal conditioning strategy to align the generative flow path with historical context and employs action-centroid guided filtering to dynamically assess and integrate outputs. Extensive experiments demonstrate that FlowDec outperforms state-of-the-art decorruption methods in both navigation accuracy and generation latency. Our approach establishes a robust, efficient paradigm for resilient embodied navigation in unpredictable real-world conditions.

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Yufei Zhang, Changhao Chen. 2026-06-21. FlowDec: Temporal Conditional Flow Decorruptor for Robust Continuous Vision-Language Navigation. https://arxiv.org/abs/2606.22424

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