output
20202025
most citedTransductive Information Maximization For Few-Shot Learning

49 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2024Show all

4 papers · 1 filter

cs.CL2024

Part-Of-Speech Sensitivity of Routers in Mixture of Experts Models

Elie Antoine, Frédéric Béchet, Philippe Langlais

This study investigates the behavior of model-integrated routers in Mixture of Experts (MoE) models, focusing on how tokens are routed based on their linguistic features, specifica…

cs.LG2024

Exposing the Vulnerability of Decentralized Learning to Membership Inference Attacks Through the Lens of Graph Mixing

Ousmane Touat, Jezekael Brunon, Yacine Belal +4

The primary promise of decentralized learning is to allow users to engage in the training of machine learning models in a collaborative manner while keeping their data on their pre…

cs.LG2024

Beyond the Norms: Detecting Prediction Errors in Regression Models

Andres Altieri, Marco Romanelli, Georg Pichler +2

This paper tackles the challenge of detecting unreliable behavior in regression algorithms, which may arise from intrinsic variability (e.g., aleatoric uncertainty) or modeling err…

cs.CL2024

WikiFactDiff: A Large, Realistic, and Temporally Adaptable Dataset for Atomic Factual Knowledge Update in Causal Language Models

Hichem Ammar Khodja, Frédéric Béchet, Quentin Brabant +2

The factuality of large language model (LLMs) tends to decay over time since events posterior to their training are "unknown" to them. One way to keep models up-to-date could be fa…