Challenges in Grounding Language in the Real World

A long-term goal of Artificial Intelligence is to build a language understanding system that allows a human to collaborate with a physical robot using language that is natural to the human. In this paper we highlight some of the challenges in doing this, and propose a solution that integrates the abilities of a cognitive agent capable of interactive task learning in a physical robot with the linguistic abilities of a large language model. We also point the way to an initial implementation of this approach.

Publication Details

Journal
ArXiv.org
Published
2025-06-20
Primary Topic
Multimodal Machine Learning Applications
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article

Challenges in Grounding Language in the Real World

ArXiv.org
Multimodal Machine Learning Applications
article

Challenges in Grounding Language in the Real World

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Abstract

A long-term goal of Artificial Intelligence is to build a language understanding system that allows a human to collaborate with a physical robot using language that is natural to the human. In this paper we highlight some of the challenges in doing this, and propose a solution that integrates the abilities of a cognitive agent capable of interactive task learning in a physical robot with the linguistic abilities of a large language model. We also point the way to an initial implementation of this approach.

ArXiv.org
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Multimodal Machine Learning Applications
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Challenges in Grounding Language in the Real World · ArXiv.org (2025) | TGRS Research Map | TGRS