@InProceedings{volchek-poritski:2026:wmt,
  author    = {Volchek, Oksana  and  Poritski, Vladislav},
  title     = {Krosny at WMT26 General Translation Task: Dictionary Augmentation and Iterative Refinement for English–Belarusian Translation},
  booktitle      = {Proceedings of the Eleventh Conference on Machine Translation},
  month          = {October},
  year           = {2026},
  address        = {Budapest, Hungary},
  publisher      = {Association for Computational Linguistics},
  pages     = {1432--1436},
  abstract  = {This paper describes our submission to the WMT26 General Machine Translation shared task for the English → Belarusian direction. In lower-resourced morphologically rich languages like Belarusian, open-weight large language models (LLMs) frequently struggle with orthographic fidelity, hallucinated vocabulary, and negative transfer from related high-resource languages. To address these issues, we implemented Krosny, an iterative, resource-augmented pipeline built on top of TranslateGemma 12B. The system translates each segment in three stages: (1) dictionary-augmented generation, (2) refinement using a reference grammatical database, and (3) rule-based post-processing followed by an LLM-as-a-judge candidate selection. We find a small but consistent improvement over the baseline TranslateGemma 12B. In comparison with other constrained-track systems of WMT26, the performance of Krosny is mid-tier. We release the source code of our implementation (https://github.com/volchek/Krosny-WMT26).},
  url       = {https://aclanthology.org/2026.wmt-1.80}
}