7 citations · 12 across the 3 of their papers we have counts for
3 papers
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…
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…
OutfitTransformer: Learning Outfit Representations for Fashion Recommendation
Rohan Sarkar, Navaneeth Bodla, Mariya I. Vasileva +4
Learning an effective outfit-level representation is critical for predicting the compatibility of items in an outfit, and retrieving complementary items for a partial outfit. We pr…