Tradutor: Building a Variety Specific Translation Model
Hugo O. Sousa, Satya Almasian, Ricardo Campos, Alípio Mário Jorge
Abstract
Language models have become foundational to many widely used systems. However, these seemingly advantageous models are double-edged swords. While they excel in tasks related to resource-rich languages like English, they often lose the fine nuances of language forms, dialects, and varieties that are inherent to languages spoken in multiple regions of the world. Languages like European Portuguese are neglected in favor of their more popular counterpart, Brazilian Portuguese, leading to suboptimal performance in various linguistic tasks. To address this gap, we introduce the first open-source translation model specifically tailored for European Portuguese, along with a novel dataset specifically designed for this task. Results from automatic evaluations on two benchmark datasets demonstrate that our best model surpasses existing open-source translation systems for Portuguese and approaches the performance of industry-leading closed-source systems for European Portuguese. By making our dataset, models, and code publicly available, we aim to support and encourage further research, fostering advancements in the representation of underrepresented language varieties.
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Builds on5
- LoRA: Low-Rank Adaptation of Large Language ModelsEdward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu et al.ICLR 2022 · 18,833 citations
- QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language ModelsYuhui Xu, Lingxi Xie, Xiaotao Gu, Xin Chen et al.ICLR 2024 · 179 citations
- Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for CatalanJordi Armengol-Estapé, Casimiro Pio Carrino, Carlos Rodríguez Penagos, Ona De Gibert Bonet et al.ACL Findings 2021 · 21 citations
- COMET: A Neural Framework for MT EvaluationRicardo Rei, Craig Stewart, Ana C. Farinha, Alon LavieEMNLP 2020 · 6 citations
- Enhancing Portuguese Variety Identification with Cross-Domain ApproachesHugo O. Sousa, Rúben Almeida, Purificação Silvano, Inês Cantante et al.AAAI 2025 · 4 citations
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