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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2506.17375 |
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| _version_ | 1866908415094161408 |
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| author | Lindes, Peter Skiker, Kaoutar |
| author_facet | Lindes, Peter Skiker, Kaoutar |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_17375 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Challenges in Grounding Language in the Real World Lindes, Peter Skiker, Kaoutar Neurons and Cognition Artificial Intelligence 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. |
| title | Challenges in Grounding Language in the Real World |
| topic | Neurons and Cognition Artificial Intelligence |
| url | https://arxiv.org/abs/2506.17375 |