18 citations · 89 across the 18 of their papers we have counts for
18 papers
AMALIA Technical Report: A Fully Open Source Large Language Model for European Portuguese
Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos +19
Despite rapid progress in open large language models (LLMs), European Portuguese (pt-PT) remains underrepresented in both training data and native evaluation, with machine-translat…
EuroLLM-9B: Technical Report
Pedro Henrique Martins, João Alves, Patrick Fernandes +14
This report presents EuroLLM-9B, a large language model trained from scratch to support the needs of European citizens by covering all 24 official European Union languages and 11 a…
EuroLLM: Multilingual Language Models for Europe
Pedro Henrique Martins, Patrick Fernandes, João Alves +12
The quality of open-weight LLMs has seen significant improvement, yet they remain predominantly focused on English. In this paper, we introduce the EuroLLM project, aimed at develo…
Is Context Helpful for Chat Translation Evaluation?
Sweta Agrawal, Amin Farajian, Patrick Fernandes +2
Despite the recent success of automatic metrics for assessing translation quality, their application in evaluating the quality of machine-translated chats has been limited. Unlike…
SaulLM-7B: A pioneering Large Language Model for Law
Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf +8
In this paper, we introduce SaulLM-7B, a large language model (LLM) tailored for the legal domain. With 7 billion parameters, SaulLM-7B is the first LLM designed explicitly for leg…
Tower: An Open Multilingual Large Language Model for Translation-Related Tasks
Duarte M. Alves, José Pombal, Nuno M. Guerreiro +10
While general-purpose large language models (LLMs) demonstrate proficiency on multiple tasks within the domain of translation, approaches based on open LLMs are competitive only wh…
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…
Steering Large Language Models for Machine Translation with Finetuning and In-Context Learning
Duarte M. Alves, Nuno M. Guerreiro, João Alves +5
Large language models (LLMs) are a promising avenue for machine translation (MT). However, current LLM-based MT systems are brittle: their effectiveness highly depends on the choic…
xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection
Nuno M. Guerreiro, Ricardo Rei, Daan van Stigt +3
Widely used learned metrics for machine translation evaluation, such as COMET and BLEURT, estimate the quality of a translation hypothesis by providing a single sentence-level scor…
Conformalizing Machine Translation Evaluation
Chrysoula Zerva, André F. T. Martins
Several uncertainty estimation methods have been recently proposed for machine translation evaluation. While these methods can provide a useful indication of when not to trust mode…
CREST: A Joint Framework for Rationalization and Counterfactual Text Generation
Marcos Treviso, Alexis Ross, Nuno M. Guerreiro +1
Selective rationales and counterfactual examples have emerged as two effective, complementary classes of interpretability methods for analyzing and training NLP models. However, pr…
The Inside Story: Towards Better Understanding of Machine Translation Neural Evaluation Metrics
Ricardo Rei, Nuno M. Guerreiro, Marcos Treviso +3
Neural metrics for machine translation evaluation, such as COMET, exhibit significant improvements in their correlation with human judgments, as compared to traditional metrics bas…
Hallucinations in Large Multilingual Translation Models
Nuno M. Guerreiro, Duarte Alves, Jonas Waldendorf +4
Large-scale multilingual machine translation systems have demonstrated remarkable ability to translate directly between numerous languages, making them increasingly appealing for r…
Optimal Transport for Unsupervised Hallucination Detection in Neural Machine Translation
Nuno M. Guerreiro, Pierre Colombo, Pablo Piantanida +1
Neural machine translation (NMT) has become the de-facto standard in real-world machine translation applications. However, NMT models can unpredictably produce severely pathologica…
Chunk-based Nearest Neighbor Machine Translation
Pedro Henrique Martins, Zita Marinho, André F. T. Martins
Semi-parametric models, which augment generation with retrieval, have led to impressive results in language modeling and machine translation, due to their ability to retrieve fine-…
Efficient Machine Translation Domain Adaptation
Pedro Henrique Martins, Zita Marinho, André F. T. Martins
Machine translation models struggle when translating out-of-domain text, which makes domain adaptation a topic of critical importance. However, most domain adaptation methods focus…
Disentangling Uncertainty in Machine Translation Evaluation
Chrysoula Zerva, Taisiya Glushkova, Ricardo Rei +1
Trainable evaluation metrics for machine translation (MT) exhibit strong correlation with human judgements, but they are often hard to interpret and might produce unreliable scores…
Uncertainty-Aware Machine Translation Evaluation
Taisiya Glushkova, Chrysoula Zerva, Ricardo Rei +1
Several neural-based metrics have been recently proposed to evaluate machine translation quality. However, all of them resort to point estimates, which provide limited information…