FreLLM4Rec shows that LLMs attenuate low-frequency collaborative components of item embeddings and introduces graph and temporal low-pass filters that preserve them, achieving up to 8% NDCG@10 gains.
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Beyond Semantic Understanding: Preserving Collaborative Frequency Components in LLM-based Recommendation
FreLLM4Rec shows that LLMs attenuate low-frequency collaborative components of item embeddings and introduces graph and temporal low-pass filters that preserve them, achieving up to 8% NDCG@10 gains.