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DialNav: Multi-turn Dialog Navigation with a Remote Guide

About

We introduce DialNav, a novel collaborative embodied dialog task, where a navigation agent (Navigator) and a remote guide (Guide) engage in multi-turn dialog to reach a goal location. Unlike prior work, DialNav aims for holistic evaluation and requires the Guide to infer the Navigator's location, making communication essential for task success. To support this task, we collect and release the Remote Assistance in Navigation (RAIN) dataset, human-human dialog paired with navigation trajectories in photorealistic environments. We design a comprehensive benchmark to evaluate both navigation and dialog, and conduct extensive experiments analyzing the impact of different Navigator and Guide models. We highlight key challenges and publicly release the dataset, code, and evaluation framework to foster future research in embodied dialog.

Leekyeung Han, Hyunji Min, Gyeom Hwangbo, Jonghyun Choi, Paul Hongsuck Seo• 2025

Related benchmarks

TaskDatasetResultRank
Vision-and-Dialogue NavigationRAIN Seen (val)
Success Rate (SR)30.77
5
Vision-and-Dialogue NavigationRAIN (val unseen)
Success Rate (SR)14.52
5
Human-agent cooperation navigationDial-Nav seen (val)
Success Rate47.8
4
Human-agent cooperation navigationDial-Nav unseen (val)
Success Rate14.3
4
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