  We address the challenging task of Localization via Embodied Dialog (LED).
Given a dialog from two agents, an Observer navigating through an unknown
environment and a Locator who is attempting to identify the Observer's
location, the goal is to predict the Observer's final location in a map. We
develop a novel LED-Bert architecture and present an effective pretraining
strategy. We show that a graph-based scene representation is more effective
than the top-down 2D maps used in prior works. Our approach outperforms
previous baselines.
