Kai-Qi Liu

Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens

Characterizing users and items through vector representations is crucial for various tasks in recommender systems. Recent approaches attempt to apply Large Language Models (LLMs) in recommendation through a question\&answer format, where real items (eg, Item No.2024) are represented with compound wo…