1 citations · 1 across the 3 of their papers we have counts for
3 papers
Does It Make Sense to Explain a Black Box With Another Black Box?
Julien Delaunay, Luis Galárraga, Christine Largouët
Although counterfactual explanations are a popular approach to explain ML black-box classifiers, they are less widespread in NLP. Most methods find those explanations by iterativel…
s-LIME: Reconciling Locality and Fidelity in Linear Explanations
Romaric Gaudel, Luis Galárraga, Julien Delaunay +2
The benefit of locality is one of the major premises of LIME, one of the most prominent methods to explain black-box machine learning models. This emphasis relies on the postulate…
REMI: Mining Intuitive Referring Expressions on Knowledge Bases
Luis Galárraga, Julien Delaunay, Jean-Louis Dessalles
A referring expression (RE) is a description that identifies a set of instances unambiguously. Mining REs from data finds applications in natural language generation, algorithmic j…