9 citations · 24 across the 6 of their papers we have counts for
6 papers
The Lucie-7B LLM and the Lucie Training Dataset: Open resources for multilingual language generation
Olivier Gouvert, Julie Hunter, Jérôme Louradour +6
We present both the Lucie Training Dataset and the Lucie-7B foundation model. The Lucie Training Dataset is a multilingual collection of textual corpora centered around French and…
TEARS: Textual Representations for Scrutable Recommendations
Emiliano Penaloza, Olivier Gouvert, Haolun Wu +1
Traditional recommender systems rely on high-dimensional (latent) embeddings for modeling user-item interactions, often resulting in opaque representations that lack interpretabili…
A Comparative Study of Gamma Markov Chains for Temporal Non-Negative Matrix Factorization
Louis Filstroff, Olivier Gouvert, Cédric Févotte +1
Non-negative matrix factorization (NMF) has become a well-established class of methods for the analysis of non-negative data. In particular, a lot of effort has been devoted to pro…
Ordinal Non-negative Matrix Factorization for Recommendation
Olivier Gouvert, Thomas Oberlin, Cédric Févotte
We introduce a new non-negative matrix factorization (NMF) method for ordinal data, called OrdNMF. Ordinal data are categorical data which exhibit a natural ordering between the ca…
Recommendation from Raw Data with Adaptive Compound Poisson Factorization
Olivier Gouvert, Thomas Oberlin, Cédric Févotte
Count data are often used in recommender systems: they are widespread (song play counts, product purchases, clicks on web pages) and can reveal user preference without any explicit…
Negative Binomial Matrix Factorization for Recommender Systems
Olivier Gouvert, Thomas Oberlin, Cédric Févotte
We introduce negative binomial matrix factorization (NBMF), a matrix factorization technique specially designed for analyzing over-dispersed count data. It can be viewed as an exte…