10 citations · 10 across the 3 of their papers we have counts for
3 papers
Interference Matrix: Quantifying Cross-Lingual Interference in Transformer Encoders
Belen Alastruey, João Maria Janeiro, Alexandre Allauzen +3
In this paper, we present a comprehensive study of language interference in encoder-only Transformer models across 83 languages. We construct an interference matrix by training and…
Large Concept Models: Language Modeling in a Sentence Representation Space
LCM team, Loïc Barrault, Paul-Ambroise Duquenne +18
LLMs have revolutionized the field of artificial intelligence and have emerged as the de-facto tool for many tasks. The current established technology of LLMs is to process input a…
MEXMA: Token-level objectives improve sentence representations
João Maria Janeiro, Benjamin Piwowarski, Patrick Gallinari +1
Current pre-trained cross-lingual sentence encoders approaches use sentence-level objectives only. This can lead to loss of information, especially for tokens, which then degrades…