Papers by Chenxin Jin
LLM-REDIAL: A Large-Scale Dataset for Conversational Recommender Systems Created from User Behaviors with LLMs (2024.findings-acl)
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| Challenge: | Existing CRS datasets suffer from data inextensibility and semantic inconsistency . |
| Approach: | They introduce the LLM-REDIAL dataset to facilitate the research in CRS by leveraging large language models to generate high-quality dialogues. |
| Outcome: | The proposed dataset is the largest multi-domain CRS dataset which consists of 47.6k multi-turn dialogues with 482.6k utterances across 4 domains. |