Large Language Models (LLMs) recently demonstrated extraordinary capability in various
natural language processing (NLP) tasks including language translation, text generation …

Widely used learned metrics for machine translation evaluation, such as COMET and
BLEURT, estimate the quality of a translation hypothesis by providing a single sentence …

Widely used learned metrics for machine translation evaluation, such as Comet and Bleurt,
estimate the quality of a translation hypothesis by providing a single sentence-level score …

This paper presents the contributions of Charles University teams to the WMT23 General
translation task (English to Czech and Czech to Ukrainian translation directions). Our main …

Widely used learned metrics for machine translation evaluation, such as COMET and
BLEURT, estimate the quality of a translation hypothesis by providing a single sentence …

Minimum Bayes Risk (MBR) decoding is a powerful decoding strategy widely used for text
generation tasks, but its quadratic computational complexity limits its practical application …

Reference-based metrics that operate at the sentence level typically outperform quality
estimation metrics, which have access only to the source and system output. This is …

State-of-the-art natural language generation evaluation metrics are based on black-box
language models. Hence, recent works consider their explainability with the goals of better …

Simultaneous interpretation is an especially challenging form of translation because it
requires converting speech from one language to another in real-time. Though prior work …

This report examines methods for integrating an extended discourse context in machine
translation, focusing on neural translation methods. Machine translation systems generally …