A Systematic Evaluation of Automatic Post-editing using Large Language Models on Neural Machine Translation Output

Diplôme Master A Systematic Evaluation of Automatic Post-editing using Large Language Models on Neural Machine Translation Output eng 2025 author Yang Xiaoyan 406471 director Bouillon Pierrette 0000-0002-8854-6360 26962 Département de traitement informatique multilingue (TINFM) This master’s thesis evaluated automatic post-editing using large language models on neural machine translation outputs. The evaluation was designed to understand the results provided by different APE settings and in response to the research tasks: 1/ Evaluate and compare different APE settings (NMT+LLM) based on the quality improvements (BLEU) for machine translation; 2/ Evaluate and compare different APE settings’ effort and performance in post-editing, with a novel performance evaluation approach that assesses APE efficiency in achieving Task 1. The APE settings were from a combination of two LLMs and three NMTs. Both automatic metrics and human expert evaluation were adopted. We also proposed dividing the delta BLEU by the TER to evaluate a given APE setting’s efficiency. Although the results were consistent in both test and control groups, this metric still needs a more solid literature review, particularly in understanding the relationship between the APE’s effort and its energy consumption. NMT LLM APE Automatic metrics Human evaluation Sustainability Dewey 410.2 Maîtrise universitaire en technologies de la traduction et de la communication (MATECH) 112 Département de traitement informatique multilingue 92 false 3eb9e4dc-b330-493f-b160-78794e133dbd Master thesis Public MasterThesis_XiaoyanYang_rev_040925.pdf 3246352 application/pdf fc8a41f5a0c71e1a09674f1c8466df257aa3afa163b52a63f8e659cdbd875a71 openAccess Faculté de traduction et d'interprétation / Département de traitement informatique multilingue

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A Systematic Evaluation of Automatic Post-editing using Large Language Models on Neural Machine Translation Output				2025	64	48

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Yang, Xiaoyan

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