5 papers · 1 filter
Gender Bias in MT for a Genderless Language: New Benchmarks for Basque
Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez
Large language models (LLMs) and machine translation (MT) systems are increasingly used in our daily lives, but their outputs can reproduce gender bias present in the training data…
From SALAMANDRA to SALAMANDRATA: BSC Submission for WMT25 General Machine Translation Shared Task
Javier Garcia Gilabert, Xixian Liao, Severino Da Dalt +8
In this paper, we present the SALAMANDRATA family of models, an improved iteration of SALAMANDRA LLMs (Gonzalez-Agirre et al., 2025) specifically trained to achieve strong performa…
MT-LENS: An all-in-one Toolkit for Better Machine Translation Evaluation
Javier GarcÃa Gilabert, Carlos Escolano, Audrey Mash +2
We introduce MT-LENS, a framework designed to evaluate Machine Translation (MT) systems across a variety of tasks, including translation quality, gender bias detection, added toxic…
The power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMs
Aleix Sant, Carlos Escolano, Audrey Mash +2
This paper studies gender bias in machine translation through the lens of Large Language Models (LLMs). Four widely-used test sets are employed to benchmark various base LLMs, comp…
Investigating the translation capabilities of Large Language Models trained on parallel data only
Javier GarcÃa Gilabert, Carlos Escolano, Aleix Sant Savall +4
In recent years, Large Language Models (LLMs) have demonstrated exceptional proficiency across a broad spectrum of Natural Language Processing (NLP) tasks, including Machine Transl…