activity
20182024
most citedNeural Baselines for Word Alignment

9 citations · 19 across the 11 of their papers we have counts for

collaborators

18 papers

cs.CL2024

CroissantLLM: A Truly Bilingual French-English Language Model

Manuel Faysse, Patrick Fernandes, Nuno M. Guerreiro +13

We introduce CroissantLLM, a 1.3B language model pretrained on a set of 3T English and French tokens, to bring to the research and industrial community a high-performance, fully op…

cs.CL2023

Structural generalization in COGS: Supertagging is (almost) all you need

Alban Petit, Caio Corro, François Yvon

In many Natural Language Processing applications, neural networks have been found to fail to generalize on out-of-distribution examples. In particular, several recent semantic pars…

cs.CL2023

Towards Example-Based NMT with Multi-Levenshtein Transformers

Maxime Bouthors, Josep Crego, François Yvon

Retrieval-Augmented Machine Translation (RAMT) is attracting growing attention. This is because RAMT not only improves translation metrics, but is also assumed to implement some fo…

cs.CL2023

GlotLID: Language Identification for Low-Resource Languages

Amir Hossein Kargaran, Ayyoob Imani, François Yvon +1

Several recent papers have published good solutions for language identification (LID) for about 300 high-resource and medium-resource languages. However, there is no LID available…

cs.CL20221 cited

Graph-Based Multilingual Label Propagation for Low-Resource Part-of-Speech Tagging

Ayyoob Imani, Silvia Severini, Masoud Jalili Sabet +2

Part-of-Speech (POS) tagging is an important component of the NLP pipeline, but many low-resource languages lack labeled data for training. An established method for training a POS…

cs.CL2022

Bilingual Synchronization: Restoring Translational Relationships with Editing Operations

Jitao Xu, Josep Crego, François Yvon

Machine Translation (MT) is usually viewed as a one-shot process that generates the target language equivalent of some source text from scratch. We consider here a more general set…