Commonsense-augmented Memory Construction and Management in Long-term Conversations via Context-aware Persona Refinement
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916120916656128 |
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| author | Kim, Hana Ong, Kai Tzu-iunn Kim, Seoyeon Lee, Dongha Yeo, Jinyoung |
| author_facet | Kim, Hana Ong, Kai Tzu-iunn Kim, Seoyeon Lee, Dongha Yeo, Jinyoung |
| contents | Memorizing and utilizing speakers' personas is a common practice for response generation in long-term conversations. Yet, human-authored datasets often provide uninformative persona sentences that hinder response quality. This paper presents a novel framework that leverages commonsense-based persona expansion to address such issues in long-term conversation. While prior work focuses on not producing personas that contradict others, we focus on transforming contradictory personas into sentences that contain rich speaker information, by refining them based on their contextual backgrounds with designed strategies. As the pioneer of persona expansion in multi-session settings, our framework facilitates better response generation via human-like persona refinement. The supplementary video of our work is available at https://caffeine-15bbf.web.app/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_14215 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Commonsense-augmented Memory Construction and Management in Long-term Conversations via Context-aware Persona Refinement Kim, Hana Ong, Kai Tzu-iunn Kim, Seoyeon Lee, Dongha Yeo, Jinyoung Computation and Language Artificial Intelligence Memorizing and utilizing speakers' personas is a common practice for response generation in long-term conversations. Yet, human-authored datasets often provide uninformative persona sentences that hinder response quality. This paper presents a novel framework that leverages commonsense-based persona expansion to address such issues in long-term conversation. While prior work focuses on not producing personas that contradict others, we focus on transforming contradictory personas into sentences that contain rich speaker information, by refining them based on their contextual backgrounds with designed strategies. As the pioneer of persona expansion in multi-session settings, our framework facilitates better response generation via human-like persona refinement. The supplementary video of our work is available at https://caffeine-15bbf.web.app/. |
| title | Commonsense-augmented Memory Construction and Management in Long-term Conversations via Context-aware Persona Refinement |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2401.14215 |