Unbabel Tackles Metric Bias in AI Translation – slator.com
In a March 11, 2025 paper, Unbabel introduced MINTADJUST, a method for more accurate and reliable machine translation (MT) evaluation. MINTADJUST addresses metric interference (MINT), a phenomenon where using the same or related metrics for both model optimization and evaluation leads to over-optimistic performance estimates. The researchers identified two scenarios where MINT commonly occurs and […]
Google Expands Low-Resource AI Translation with SMOL Dataset – slator.com
On February 17, 2025, Google released SMOL (Set of Maximal Overall Leverage), a dataset translated by professional translators aimed at improving machine translation (MT) for 115 low-resource languages (LRLs). SMOL consists of two components: SMOLSENT, a collection of 863 English sentences translated into 81 languages, and SMOLDOC, a dataset of 584 English documents translated into […]