9 citations · 18 across the 5 of their papers we have counts for
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cs.AI2025★ 1 cited
From Models to Systems: A Comprehensive Fairness Framework for Compositional Recommender Systems
Brian Hsu, Cyrus DiCiccio, Natesh Sivasubramoniapillai +1
Fairness research in machine learning often centers on ensuring equitable performance of individual models. However, real-world recommendation systems are built on multiple models…
cs.AI2020★ 5 cited
A Framework for Fairness in Two-Sided Marketplaces
Kinjal Basu, Cyrus DiCiccio, Heloise Logan +1
Many interesting problems in the Internet industry can be framed as a two-sided marketplace problem. Examples include search applications and recommender systems showing people, jo…