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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.20134 |
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| _version_ | 1866929296079060992 |
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| author | Su, Megan Bao, Yuwei |
| author_facet | Su, Megan Bao, Yuwei |
| contents | Interactive Artificial Intelligent(AI) assistant systems are designed to offer timely guidance to help human users to complete a variety tasks. One of the remaining challenges is to understand user's mental states during the task for more personalized guidance. In this work, we analyze users' mental states during task executions and investigate the capabilities and challenges for large language models to interpret user profiles for more personalized user guidance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_20134 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | User Modeling Challenges in Interactive AI Assistant Systems Su, Megan Bao, Yuwei Computation and Language Interactive Artificial Intelligent(AI) assistant systems are designed to offer timely guidance to help human users to complete a variety tasks. One of the remaining challenges is to understand user's mental states during the task for more personalized guidance. In this work, we analyze users' mental states during task executions and investigate the capabilities and challenges for large language models to interpret user profiles for more personalized user guidance. |
| title | User Modeling Challenges in Interactive AI Assistant Systems |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2403.20134 |