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cs.IR2024
Leveraging Memory Retrieval to Enhance LLM-based Generative Recommendation
Chengbing Wang, Yang Zhang, Fengbin Zhu +3
Leveraging Large Language Models (LLMs) to harness user-item interaction histories for item generation has emerged as a promising paradigm in generative recommendation. However, th…
cs.IR2024★ 1 cited
Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach
Tianhao Shi, Yang Zhang, Jizhi Zhang +2
As recommender systems are indispensable in various domains such as job searching and e-commerce, providing equitable recommendations to users with different sensitive attributes b…