bibtext: @inproceedings{
  alves2024tower,
  title={Tower: An Open Multilingual Large Language Model for Translation-Related Tasks},
  author={Duarte Miguel Alves and Jos{\'e} Pombal and Nuno M Guerreiro and Pedro Henrique Martins and Jo{\~a}o Alves and Amin Farajian and Ben Peters and Ricardo Rei and Patrick Fernandes and Sweta Agrawal and Pierre Colombo and Jos{\'e} G. C. de Souza and Andre Martins},
  booktitle={First Conference on Language Modeling},
  year={2024},
  url={https://openreview.net/forum?id=EHPns3hVkj}
  }
abstract: 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 when specializing on a single task. In this paper, we propose a recipe for tailoring LLMs to multiple tasks present in translation workflows. We perform continued pretraining on a multilingual mixture of monolingual and parallel data, creating TowerBase, followed by finetuning on instructions relevant for translation processes, creating TowerInstruct. Our model surpasses open alternatives on several relevant tasks and is competitive with general-purpose closed LLMs. We will release the Tower models, our specialization dataset, an evaluation framework for LLMs focusing on the translation ecosystem, and a collection of model generations on our benchmark.
title: Tower: An Open Multilingual Large Language Model for Translation-Related Tasks
authors: Duarte Miguel Alves José Pombal Nuno M Guerreiro Pedro Henrique Martins João Alves Amin Farajian Ben Peters Ricardo Rei Patrick Fernandes Sweta Agrawal Pierre Colombo José G. C. de Souza Andre Martins