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Gonçalo Faria

2 accepted papers

2024

Modeling User Preferences with Automatic Metrics: Creating a High-Quality Preference Dataset for Machine Translation

EMNLP 2024main

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 of language nuances and context-specific variations leads to improved quality. However, preference data based on human…

2024

QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation

NeurIPS 2024poster

An important challenge in machine translation (MT) is to generate high-quality and diverse translations. Prior work has shown that the estimated likelihood from the MT model correlates poorly with translation quality. In contrast, quality evaluation metrics (such as COMET or BLEURT) exhibit high c…