10 citations · 19 across the 6 of their papers we have counts for
5 papers · 1 filter
Nonlinear Concept Erasure: a Density Matching Approach
Antoine Saillenfest, Pirmin Lemberger
Ensuring that neural models used in real-world applications cannot infer sensitive information, such as demographic attributes like gender or race, from text representations is a c…
Explaining Text Classifiers with Counterfactual Representations
Pirmin Lemberger, Antoine Saillenfest
One well motivated explanation method for classifiers leverages counterfactuals which are hypothetical events identical to real observations in all aspects except for one feature.…
Towards Scalable Adaptive Learning with Graph Neural Networks and Reinforcement Learning
Jean Vassoyan, Jill-Jênn Vie, Pirmin Lemberger
Adaptive learning is an area of educational technology that consists in delivering personalized learning experiences to address the unique needs of each learner. An important subfi…
How Graph Structure and Label Dependencies Contribute to Node Classification in a Large Network of Documents
Pirmin Lemberger, Antoine Saillenfest
We introduce a new dataset named WikiVitals which contains a large graph of 48k mutually referred Wikipedia articles classified into 32 categories and connected by 2.3M edges. Our…
A Primer on Domain Adaptation
Pirmin Lemberger, Ivan Panico
Standard supervised machine learning assumes that the distribution of the source samples used to train an algorithm is the same as the one of the target samples on which it is supp…