Abstract: Highlights•This study is the first work for history noise problem in VLN.•A novel Memory-Adaptive Model is designed to effectively adapts history noises.•Our method shows superior performances on both RxR and R2R datasets.•Our method exhibits strong adaptability across different settings.
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