Portrait de Olivier Gouvert n'est pas disponible

Olivier Gouvert

Alumni

Publications

TEARS: Text Representations for Scrutable Recommendations
Emiliano Penaloza
Olivier Gouvert
Haolun Wu
Laurent Charlin
Traditional recommender systems rely on high-dimensional (latent) embeddings for modeling user-item interactions, often resulting in opaque … (voir plus)representations that lack interpretability. Moreover, these systems offer limited control to users over their recommendations. Inspired by recent work, we introduce TExtuAl Representations for Scrutable recommendations (TEARS) to address these challenges. Instead of representing a user’s interests through latent embed- dings, TEARS encodes them in natural text, providing transparency and allowing users to edit them. To encode such preferences, we use modern LLMs to generate high-quality user summaries which we find uniquely capture user preferences. Using these summaries we take a hybrid approach where we use an optimal transport procedure to align the summaries’ representations with the repre- sentation of a standard VAE for collaborative filtering. We find this approach can surpass the performance of the three popular VAE models while providing user-controllable recommendations. We further analyze the controllability of TEARS through three simu- lated user tasks to evaluate the effectiveness of user edits on their summaries. Our code and all user-summaries can be seen in an anonymized repository.
2025-01-29
ACM.org/TheWebConf/2025/Conference (poster)
openreview.net
openreview.net