Abstract
Benchmarks do more than report scores: they provide a shared basis for evaluating methods, comparing systems, and measuring progress. As language technologies are now widely integrated into everyday life, efforts should also be made to include minority languages in the resources that underpin language-technology development. If languages are absent from relevant benchmarks, they remain harder to evaluate, compare, and incorporate into future language technologies. Expanding benchmark coverage is therefore essential for ensuring fair evaluation, increasing visibility, and enabling continued development of language technologies for these communities. To support MT development for Ladin, we contribute a Ladin extension of BOUQuET to the WMT 2026 OLDI shared task, covering the Val Badia and Gherdëina varieties. We present a systematic reference-creation workflow combining human translation, expert revision, cross-variant alignment, and blind ranking to produce high-quality references. The dataset is released (https://huggingface.co/datasets/facebook/bouquet) under the CC BY-SA 4.0 license.