activity
20242026
collaborators

5 papers

cs.LG2026

Multi-Way Representation Alignment

Akshit Achara, Tatiana Gaintseva, Mateo Mahaut +5

The Platonic Representation Hypothesis suggests that independently trained neural networks converge to increasingly similar latent spaces. However, current strategies for mapping t…

cs.CV2026

Similarity of Processing Steps in Vision Model Representations

Matéo Mahaut, Marco Baroni

Recent literature suggests that the bigger the model, the more likely it is to converge to similar, ``universal'' representations, despite different training objectives, datasets,…

cs.CL2025

A quantitative analysis of semantic information in deep representations of text and images

Santiago Acevedo, Andrea Mascaretti, Riccardo Rende +3

It was recently observed that the representations of different models that process identical or semantically related inputs tend to align. We analyze this phenomenon using the Info…

cs.CL2025

Repetitions are not all alike: distinct mechanisms sustain repetition in language models

Matéo Mahaut, Francesca Franzon

Large Language Models (LLMs) can sometimes degrade into repetitive loops, persistently generating identical word sequences. Because repetition is rare in natural human language, it…

cs.CL2024

Factual Confidence of LLMs: on Reliability and Robustness of Current Estimators

Matéo Mahaut, Laura Aina, Paula Czarnowska +3

Large Language Models (LLMs) tend to be unreliable in the factuality of their answers. To address this problem, NLP researchers have proposed a range of techniques to estimate LLM'…