2025 EMNLP EMNLP 2025

SH at WMT25 General Machine Translation Task

Abstract

AbstractI participated in the unconstrained track of the English-to-Japanese translation task at the WMT 2025 General Machine Translation Task.My submission leverages several large language models, all of which are trained with supervised fine-tuning, and some further optimized via preference learning.To enhance translation quality, I introduce an automatic post-editing model and perform automatic post-editing.In addition, I select the best translation from multiple candidates using Minimum Bayes Risk (MBR) decoding.For MBR decoding, I use COMET-22 and LaBSE-based cosine similarity as evaluation metrics.

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors