9 citations · 19 across the 8 of their papers we have counts for
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cs.IR2022
RecXplainer: Amortized Attribute-based Personalized Explanations for Recommender Systems
Sahil Verma, Chirag Shah, John P. Dickerson +3
Recommender systems influence many of our interactions in the digital world -- impacting how we shop for clothes, sorting what we see when browsing YouTube or TikTok, and determini…
cs.IR2022★ 5 cited
Contrastive Learning for Interactive Recommendation in Fashion
Karin Sevegnani, Arjun Seshadri, Tian Wang +4
Recommender systems and search are both indispensable in facilitating personalization and ease of browsing in online fashion platforms. However, the two tools often operate indepen…