7 papers
A Recipe for Long-Context Reasoning in Large Language Models via On-Policy Optimization and Distillation
Miguel Moura Ramos, Duarte M. Alves, André F. T. Martins
Existing approaches to post-train models for long-context tasks face complementary limitations: (i) supervised fine-tuning (SFT) provides stable supervision but suffers from exposu…
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-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…
Movie Facts and Fibs (MF): A Benchmark for Long Movie Understanding
Emmanouil Zaranis, António Farinhas, Saul Santos +28
Despite recent progress in vision-language models (VLMs), holistic understanding of long-form video content remains a significant challenge, partly due to limitations in current be…
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…
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…