MATRAG: Multi-Agent Transparent Retrieval-Augmented Generation for Explainable Recommendations

ArXi:2604.20848v1 Announce Type: cross Large Language Model (LLM)-based recommendation systems have nstrated remarkable capabilities in understanding user preferences and generating personalized suggestions. However, existing approaches face critical challenges in transparency, knowledge grounding, and the ability to provide coherent explanations that foster user trust. We