activity
20172025
most citedTowards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks

2 citations · 5 across the 11 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.CL2023

Toward Stronger Textual Attack Detectors

Pierre Colombo, Marine Picot, Nathan Noiry +2

The landscape of available textual adversarial attacks keeps growing, posing severe threats and raising concerns regarding the deep NLP system's integrity. However, the crucial pro…

cs.LG2023

A Novel Information-Theoretic Objective to Disentangle Representations for Fair Classification

Pierre Colombo, Nathan Noiry, Guillaume Staerman +1

One of the pursued objectives of deep learning is to provide tools that learn abstract representations of reality from the observation of multiple contextual situations. More preci…

cs.LG20231 cited

A Functional Data Perspective and Baseline On Multi-Layer Out-of-Distribution Detection

Eduardo Dadalto, Pierre Colombo, Guillaume Staerman +2

A key feature of out-of-distribution (OOD) detection is to exploit a trained neural network by extracting statistical patterns and relationships through the multi-layer classifier…

cs.DS2023

Online Matching in Geometric Random Graphs

Flore Sentenac, Nathan Noiry, Matthieu Lerasle +2

We investigate online maximum cardinality matching, a central problem in ad allocation. In this problem, users are revealed sequentially, and each new user can be paired with any p…

cs.CL20232 cited

Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks

Anas Himmi, Ekhine Irurozki, Nathan Noiry +2

The evaluation of natural language processing (NLP) systems is crucial for advancing the field, but current benchmarking approaches often assume that all systems have scores availa…