33 citations · 115 across the 13 of their papers we have counts for
16 papers
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…
Scaling up COMETKIWI: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task
Ricardo Rei, Nuno M. Guerreiro, José Pombal +5
We present the joint contribution of Unbabel and Instituto Superior Técnico to the WMT 2023 Shared Task on Quality Estimation (QE). Our team participated on all tasks: sentence- an…
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…
CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task
Ricardo Rei, Marcos Treviso, Nuno M. Guerreiro +9
We present the joint contribution of IST and Unbabel to the WMT 2022 Shared Task on Quality Estimation (QE). Our team participated on all three subtasks: (i) Sentence and Word-leve…
Towards a Sentiment-Aware Conversational Agent
Isabel Dias, Ricardo Rei, Patrícia Pereira +1
In this paper, we propose an end-to-end sentiment-aware conversational agent based on two models: a reply sentiment prediction model, which leverages the context of the dialogue to…
Quality-Aware Decoding for Neural Machine Translation
Patrick Fernandes, António Farinhas, Ricardo Rei +4
Despite the progress in machine translation quality estimation and evaluation in the last years, decoding in neural machine translation (NMT) is mostly oblivious to this and center…
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…
Onception: Active Learning with Expert Advice for Real World Machine Translation
Vânia Mendonça, Ricardo Rei, Luisa Coheur +1
Active learning can play an important role in low-resource settings (i.e., where annotated data is scarce), by selecting which instances may be more worthy to annotate. Most active…
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…
Online Learning Meets Machine Translation Evaluation: Finding the Best Systems with the Least Human Effort
Vânia Mendonça, Ricardo Rei, Luisa Coheur +2
In Machine Translation, assessing the quality of a large amount of automatic translations can be challenging. Automatic metrics are not reliable when it comes to high performing sy…
Multilingual Email Zoning
Bruno Jardim, Ricardo Rei, Mariana S. C. Almeida
The segmentation of emails into functional zones (also dubbed email zoning) is a relevant preprocessing step for most NLP tasks that deal with emails. However, despite the multilin…
Unbabel's Participation in the WMT20 Metrics Shared Task
Ricardo Rei, Craig Stewart, Catarina Farinha +1
We present the contribution of the Unbabel team to the WMT 2020 Shared Task on Metrics. We intend to participate on the segment-level, document-level and system-level tracks on all…
COMET: A Neural Framework for MT Evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha +1
We present COMET, a neural framework for training multilingual machine translation evaluation models which obtains new state-of-the-art levels of correlation with human judgements.…