Cogs in a Machine, Doing What They're Meant to Do -- The AMI Submission to the WMT24 General Translation Task
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Abstract (arXiv)
This paper presents the submission of the 'Arni Magnusson Institute's team to the WMT24 General translation task. We work on the English->Icelandic translation direction. Our system comprises four translation models and a grammar correction model. For training our models we carefully curate our datasets, aggressively filtering out sentence pairs that may detrimentally affect the quality of our system's output. Some of our data are collected from human translations and some are synthetically generated. A part of the synthetic data is generated using an LLM, and we find that it increases the translation capability of our system significantly.
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References · 16
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- 2022CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Taskcited by 205
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- 2023Scaling up COMETKIWI: Unbabel-IST 2023 Submission for the Quality Estimation Shared Taskcited by 88
- 2018On the Impact of Various Types of Noise on Neural Machine Translationcited by 76
- 2024Preliminary WMT24 Ranking of General MT Systems and LLMscited by 20
- 2023SentAlign: Accurate and Scalable Sentence Alignmentcited by 9
4 more
- 2023Byte-Level Grammatical Error Correction Using Synthetic and Curated Corporacited by 7
- 2022NMTScore: A Multilingual Analysis of Translation-based Text Similarity Measurescited by 6
- 2023Breeding Machine Translations: Evolutionary approach to survive and thrive in the world of automated evaluationcited by 5
- 2021Reranking Machine Translation Hypotheses with Structured and Web-based Language Modelscited by 2
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