HIPHOP combines LLM item embeddings, session graphs, multi-intent attention, and contrastive learning to set new state-of-the-art results on five session-based recommendation datasets.
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Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based Recommendation
HIPHOP combines LLM item embeddings, session graphs, multi-intent attention, and contrastive learning to set new state-of-the-art results on five session-based recommendation datasets.