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We present Where Are You? (WAY), a dataset of ~6k dialogs in which two humans-- an Observer and a Locator -- complete a cooperative localization task. TheObserver is spawned at random in a 3D environment and can navigate fromfirst-person views while answering questions from the Locator. The Locator mustlocalize the Observer in a detailed top-down map by asking questions and givinginstructions. Based on this dataset, we define three challenging tasks:Localization from Embodied Dialog or LED (localizing the Observer from dialoghistory), Embodied Visual Dialog (modeling the Observer), and CooperativeLocalization (modeling both agents). In this paper, we focus on the LED task --providing a strong baseline model with detailed ablations characterizing bothdataset biases and the importance of various modeling choices. Our best modelachieves 32.7% success at identifying the Observer's location within 3m inunseen buildings, vs. 70.4% for human Locators.

Where Are You? Localization from Embodied Dialog