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Found 3 papers, 3 papers with code
To Recommend or Not: Recommendability Identification in Conversations with Pre-trained Language Models
First, we propose and define the recommendability identification task, which investigates the need for recommendations in the current conversational context.
Multi-Agent Collaboration Framework for Recommender Systems
LLM-based agents have gained considerable attention for their decision-making skills and ability to handle complex tasks.
Intent-aware Ranking Ensemble for Personalized Recommendation
To address such a task, we propose an Intent-aware ranking Ensemble Learning~(IntEL) model to fuse multiple single-objective item lists with various user intents, in which item-level personalized weights are learned.
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