mlsanityData to 14 Oct 2026

An Automatic Evaluation of the WMT22 General Machine Translation Task

arXiv 2209.14172 ↗First posted 28 Sep 2022cs.CLcited by 1

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Abstract (arXiv)

This report presents an automatic evaluation of the general machine translation task of the Seventh Conference on Machine Translation (WMT22). It evaluates a total of 185 systems for 21 translation directions including high-resource to low-resource language pairs and from closely related to distant languages. This large-scale automatic evaluation highlights some of the current limits of state-of-the-art machine translation systems. It also shows how automatic metrics, namely chrF, BLEU, and COMET, can complement themselves to mitigate their own limits in terms of interpretability and accuracy.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 7 references that are in the map. First posted on arXiv 28 Sep 2022.

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2 of 7 references.

References · 2

  1. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,799
  2. 2020COMET: A Neural Framework for MT Evaluationcited by 1,033

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