Amazon

The 'Amazon' dataset is a benchmark that contains user behavior data used to evaluate the performance of recommender systems, particularly in the context of collaborative filtering and memory evolution techniques.

Papers using Amazon (9)

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation2026AMEM4Rec: Leveraging Cross-User Similarity for Memory Evolution in Agentic LLM Recommenders2026Reasoning-guided Collaborative Filtering with Language Models for Explainable Recommendation2026Reasoning to Rank: An End-to-End Solution for Exploiting Large Language Models for Recommendation2026ExplainRec: Towards Explainable Multi-Modal Zero-Shot Recommendation with Preference Attribution and Large Language Models2025Iterative Critique-Refine Framework for Enhancing LLM Personalization2025X-Cross: Dynamic Integration of Language Models for Cross-Domain Sequential Recommendation2025LLM-based User Profile Management for Recommender System2025LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering2024