# SpatialNav: Leveraging Spatial Scene Graphs for Zero-Shot Vision-and-Language Navigation Source: [SpatialNav: Leveraging Spatial Scene Graphs for Zero-Shot Vision-and-Language Navigation]() Collection index: [llms.txt]() Data updated: 2026-01-14T05:00:04.658Z Authors: Jiwen Zhang, Zejun Li, Siyuan Wang, Xiangyu Shi, Zhongyu Wei, Qi Wu Published: 2026-01-11T08:39:19.000Z ## Abstract Although learning-based vision-and-language navigation (VLN) agents can learn spatial knowledge implicitly from large-scale training data, zero-shot VLN agents lack this process, relying primarily on local observations for navigation, which leads to inefficient exploration and a significant performance gap. To deal with the problem, we consider a zero-shot VLN setting that agents are allowed to fully explore the environment before task execution. Then, we construct the Spatial Scene Graph (SSG) to explicitly capture global spatial structure and semantics in the explored environment. Based on the SSG, we introduce SpatialNav, a zero-shot VLN agent that integrates an agent-centric spatial map, a compass-aligned visual representation, and a remote object localization strategy for efficient navigation. Comprehensive experiments in both discrete and continuous environments demonstrate that SpatialNav significantly outperforms existing zero-shot agents and clearly narrows the gap with state-of-the-art learning-based methods. Such results highlight the importance of global spatial representations for generalizable navigation. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Vision-and-Language Navigation on REVERIE Unseen Discrete (val)](): Vision-and-Language Navigation; REVERIE Unseen Discrete (val); OSR: 58.1. - [Vision-and-Language Navigation on R2R-CE unseen continuous (val)](): Vision-and-Language Navigation; R2R-CE unseen continuous (val); SR: 64. - [Vision-Language Navigation on R2R-CE (val-unseen)](): Vision-Language Navigation; R2R-CE (val-unseen); Success Rate (SR): 68. - [Vision-and-Language Navigation on R2R Discrete (val-unseen)](): Vision-and-Language Navigation; R2R Discrete (val-unseen); Navigation Error (NE): 4.4. - [Vision-Language Navigation on RxR-CE (val-unseen)](): Vision-Language Navigation; RxR-CE (val-unseen); SR: 39. ## Original sources and implementation [Original paper]() [PDF]()