@InProceedings{zhang-EtAl:2026:wmt1,
  author    = {Zhang, Fan  and  Mei, Tu  and  Mengchao, Zhang  and  Wu, Jinting  and  Zhang, Bowbjut.edu.cnen},
  title     = {TaT at WMT26 Terminology Translation Shared Task},
  booktitle      = {Proceedings of the Eleventh Conference on Machine Translation},
  month          = {October},
  year           = {2026},
  address        = {Budapest, Hungary},
  publisher      = {Association for Computational Linguistics},
  pages     = {1899--1905},
  abstract  = {The accurate translation of domain-specific terminology remains a critical bottleneck for ensuring the fidelity and professionalism of machine translation systems. This paper presents our submission to the WMT26 Terminology Translation Shared Task: the TaT (Terminology-aware Translation) system. Built upon a structured, pipelined architecture, TaT integrates five specialized components designed to seamlessly ingest, process, and translate ambiguous textual inputs while strictly adhering to targeted terminology dictionary. Specifically, the framework comprises a sentence splitter, a terminology retriever, a lexical disambiguator, a baseline translator, and a dedicated terminology extractor tailored for Track 2 constraints. Both internal benchmarking and ablation studies demonstrate that our decoupled pipeline delivers robust performance, successfully meeting design expectations and substantially mitigating terminology omission and misalignment errors in domain-specific translations.},
  url       = {https://aclanthology.org/2026.wmt-1.124}
}