Источник
NeurIPS Workshop
Дата публикации
21.03.2022
Авторы
Михаил Бурцев Александр Панов Алексей Скрынник Артем Жолус Shrestha Mohanty Юлия Киселева 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.

Аннотация

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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