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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'…