8 citations · 17 across the 15 of their papers we have counts for
16 papers · 1 filter
EuroLLM-22B: Technical Report
Miguel Moura Ramos, Duarte M. Alves, Hippolyte Gisserot-Boukhlef +15
This report presents EuroLLM-22B, a large language model trained from scratch to support the needs of European citizens by covering all 24 official European Union languages and 11…
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…
Multilingual Contextualization of Large Language Models for Document-Level Machine Translation
Miguel Moura Ramos, Patrick Fernandes, Sweta Agrawal +1
Large language models (LLMs) have demonstrated strong performance in sentence-level machine translation, but scaling to document-level translation remains challenging, particularly…
Do LLMs Understand Your Translations? Evaluating Paragraph-level MT with Question Answering
Patrick Fernandes, Sweta Agrawal, Emmanouil Zaranis +2
Despite the steady progress in machine translation evaluation, existing automatic metrics struggle to capture how well meaning is preserved beyond sentence boundaries. We posit tha…
M-Prometheus: A Suite of Open Multilingual LLM Judges
José Pombal, Dongkeun Yoon, Patrick Fernandes +5
The use of language models for automatically evaluating long-form text (LLM-as-a-judge) is becoming increasingly common, yet most LLM judges are optimized exclusively for English,…
EuroBERT: Scaling Multilingual Encoders for European Languages
Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves +16
General-purpose multilingual vector representations, used in retrieval, regression and classification, are traditionally obtained from bidirectional encoder models. Despite their w…
A Context-aware Framework for Translation-mediated Conversations
José Pombal, Sweta Agrawal, Patrick Fernandes +2
Automatic translation systems offer a powerful solution to bridge language barriers in scenarios where participants do not share a common language. However, these systems can intro…
Fine-Grained Reward Optimization for Machine Translation using Error Severity Mappings
Miguel Moura Ramos, Tomás Almeida, Daniel Vareta +4
Reinforcement learning (RL) has been proven to be an effective and robust method for training neural machine translation systems, especially when paired with powerful reward models…
Modeling User Preferences with Automatic Metrics: Creating a High-Quality Preference Dataset for Machine Translation
Sweta Agrawal, José G. C. de Souza, Ricardo Rei +5
Alignment with human preferences is an important step in developing accurate and safe large language models. This is no exception in machine translation (MT), where better handling…
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…
Thesis proposal: Are We Losing Textual Diversity to Natural Language Processing?
Josef Jon
This thesis argues that the currently widely used Natural Language Processing algorithms possibly have various limitations related to the properties of the texts they handle and pr…
DOCE: Finding the Sweet Spot for Execution-Based Code Generation
Haau-Sing Li, Patrick Fernandes, Iryna Gurevych +1
Recently, a diverse set of decoding and reranking procedures have been shown effective for LLM-based code generation. However, a comprehensive framework that links and experimental…
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…
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…
Context-aware Neural Machine Translation for English-Japanese Business Scene Dialogues
Sumire Honda, Patrick Fernandes, Chrysoula Zerva
Despite the remarkable advancements in machine translation, the current sentence-level paradigm faces challenges when dealing with highly-contextual languages like Japanese. In thi…