24 citations · 71 across the 16 of their papers we have counts for
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cs.IR2023
LTP-MMF: Towards Long-term Provider Max-min Fairness Under Recommendation Feedback Loops
Chen Xu, Xiaopeng Ye, Jun Xu +3
Multi-stakeholder recommender systems involve various roles, such as users, and providers. Previous work pointed out that max-min fairness (MMF) is a better metric to support weak…
cs.GT2023
Sequential Persuasion Using Limited Experiments
Bonan Ni, Weiran Shen, Pingzhong Tang
Bayesian persuasion and its derived information design problem has been one of the main research agendas in the economics and computation literature over the past decade. However,…
cs.IR2023★ 3 cited
P-MMF: Provider Max-min Fairness Re-ranking in Recommender System
Chen Xu, Sirui Chen, Jun Xu +4
In this paper, we address the issue of recommending fairly from the aspect of providers, which has become increasingly essential in multistakeholder recommender systems. Existing s…