Continual Graph Memory for Adaptive Recommendation under Intent Drift
Experiments across multiple recommendation settings show that CGM-Rec improves over evaluated neural and LLM-based baselines on most metrics, and under sampled-candidate reranking, CGM-Rec improves HR@1 by up to 29.58% over the strongest LLM baseline on Bundle, and outperforms K-RagRec on metadata-rich ML-100K.
Hao Nguyen Ngoc, T. Nguyen, Hanh Thi Nguyen et al.
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