SOURCE-LINKED INTELLIGENCE
In the Blind: Building Pseudo-References for MT Evaluation
The WMT26 General MT task evaluates systems on 10 language pairs that have no human references (neither translated from scratch nor post-edited from MT output by humans). We describe how we built the pseudo-references for these pairs and six other language pairs (in which some forms of human references are available): seven models translate the 3,277 official documents under up to five prompt conditions, giving a total of 26 system-prompt combinations; then three reference-free quality estimation (QE) models score every candidate; and a per-document selector picks one translation, which GPT-5.
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-11T23:54:29.000Z
First collected: 2026-09-20T16:41:15.630Z. This is not the publication date.