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Found 3 papers, 3 papers with code
Doing Personal LAPS: LLM-Augmented Dialogue Construction for Personalized Multi-Session Conversational Search
Our results show that responses generated explicitly using extracted preferences better match user's actual preferences, highlighting the value of using extracted preferences over simple dialogue history.
Personal Entity, Concept, and Named Entity Linking in Conversations
It is, however, shown that existing EL methods developed for annotating documents are suboptimal for conversations, where personal entities (e. g., "my cars") and concepts are essential for understanding user utterances.
Conversational Entity Linking: Problem Definition and Datasets
Further, we report on the performance of traditional EL systems on our Conversational Entity Linking dataset, ConEL, and present an extension to these methods to better fit the conversational setting.
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