Marco de Gemmis

Integrating Heterogeneous Knowledge for Enhanced Recommendation with Large Language Models

The proposed REKALM, a comprehensive integration framework for enhancing LLM-based recommenders through knowledge integration, demonstrates that augmenting LLMs with lexicalized, domain-specific knowledge is an effective system-level strategy for advancing the next generation of recommender systems.