ru
ru
Source
NeurIPS Workshop
DATE OF PUBLICATION
03/21/2022
Authors
Mikhail Burtsev Alexander Panov Alexey Skrynnik Artem Zholus Shrestha Mohanty Julia Kiseleva Kavya Srinet Arthur Szlam Yuxuan Sun Marc-Alexandre Cotˆe Negar Arabzadeh Milagro Teruel
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Collecting Interactive Multi-modal Datasets for Grounded Language Understanding.

Abstract

Human intelligence can remarkably adapt quickly to new tasks and environments. Starting from a very young age, humans acquire new skills and learn how to solve new tasks either by imitating the behavior of others or by following provided natural language instructions. To facilitate research which can enable similar capabilities in machines, we made the following contributions (1) formalized the collaborative embodied agent using natural language task; (2) developed a tool for extensive and scalable data collection; and (3) collected the first dataset for interactive grounded language understanding.

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