Multi-Source Multi-Type Knowledge Exploration and Exploitation for Dialogue Generation (2023.emnlp-main)
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| Challenge: | Existing models focus on identifying specific types of dialogue knowledge and utilizing corresponding datasets for training, but lack generalization capabilities and computational resources. |
| Approach: | They propose a framework that explores multi-source multi-type knowledge from LLMs by leveraging diverse datasets and exploits it for response generation. |
| Outcome: | The proposed framework exploits multi-source multi-type knowledge from LLMs to generate coherent, informative, and fluent responses. |
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