Combining Unsupervised and Supervised Learning for Sample Efficient Continuous Language Grounding

Natural and efficient communication with humans requires artificial agents that are able to understand the meaning of natural language. However, understanding natural language is non-trivial and requires proper grounding mechanisms to create links between words and corresponding perceptual informati...

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Detalhes bibliográficos

Autor principal:	Oliver Roesler
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2022-09-01
coleção:	Frontiers in Robotics and AI
Assuntos:	language grounding cross-situational learning interactive learning sample efficiency human-agent interaction CLEVR
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/frobt.2022.701250/full
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