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LuxMT Technical Report

arXiv 2602.15506 ↗First posted 17 Feb 2026cs.CLcited by 0

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Abstract (arXiv)

We introduce LuxMT, a machine translation system based on Gemma 3 27B and fine-tuned for translation from Luxembourgish (LB) into French (FR) and English (EN). To assess translation performance, we construct a novel benchmark covering LB-FR, LB-EN, and LB-FR using human-translated data from Luci, a tourist magazine about Luxembourg. Training data stems from LuxAlign, a parallel corpus of multilingual Luxembourgish news articles, and LB parliamentary transcripts augmented with Google Translate. We filter the data using LuxEmbedder, LB sentence embeddings, to remove low-equivalence segment-pairs. Overall, LuxMT's results suggest strong improvements over the Gemma 3 baseline, even for translating LB to German (DE), despite the training data not containing any DE. We also explore LuxEmbedder's potential to be used as a quality estimation metric and find strong correlations with other reference-based metrics. However, we call for further research to fully assess the metric's utility and advise using it with caution.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 19 references that are in the map. First posted on arXiv 17 Feb 2026.

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9 of 19 references.

References · 9

  1. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  2. 2022No Language Left Behind: Scaling Human-Centered Machine Translationcited by 1,312
  3. 2023xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detectioncited by 265
  4. 2021Learning Compact Metrics for MTcited by 93
  5. 2023Towards a Common Understanding of Contributing Factors for Cross-Lingual Transfer in Multilingual Language Models: A Reviewcited by 50
  6. 2024Navigating the Metrics Maze: Reconciling Score Magnitudes and Accuraciescited by 40
  7. 2024Machine Translation Meta Evaluation through Translation Accuracy Challenge Setscited by 18
  8. 2025MetricX-25 and GemSpanEval: Google Translate Submissions to the WMT25 Evaluation Shared Taskcited by 10
  9. 2024LuxEmbedder: A Cross-Lingual Approach to Enhanced Luxembourgish Sentence Embeddingscited by 7

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