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SalamandraTA

model1 events
papersSEP 10 04:00 UTC

SalamandraTA Paper Uses Hard Examples for WMT 2026 Terminology Translation Task

Researchers describe SalamandraTA, their entry for the WMT 2026 shared task on terminology-aware translation, where outputs must exactly match glossary-prescribed terms. The paper argues that fine-tuning on all glossary-annotated translation pairs is inefficient and proposes prioritizing hard examples during training. The work is available as an arXiv preprint.

machine-translation/terminology/wmt/fine-tuning