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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