RevBrowse retrieves preference-relevant pros and cons from reviews via a contrastively trained module, then uses an LLM to rerank candidates; experiments on four Amazon datasets show consistent improvements over baselines.
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Learning to Shop Like Humans: A Review-driven Retrieval-Augmented Recommendation Framework with LLMs
RevBrowse retrieves preference-relevant pros and cons from reviews via a contrastively trained module, then uses an LLM to rerank candidates; experiments on four Amazon datasets show consistent improvements over baselines.