Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences

Traditional recommender systems leverage users' item preference history to recommend novel content that users may like. However, modern dialog interfaces that allow users to express language-based preferences offer a fundamentally different modality for preference input. Inspired by recent succ...

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Bibliographische Detailangaben

Hauptverfasser:	Sanner, Scott, Balog, Krisztian, Radlinski, Filip, Wedin, Ben, Dixon, Lucas
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Information Retrieval Computer Science - Learning
Online-Zugang:	Volltext bestellen
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