Textual overlap rather than domain alignment: A comparative study of fine-tuning strategies for specialised machine translation with large language models.
- DOI
- 10.1371/journal.pone.0352256
- Published
- 2026-07-20
- Container
- PLoS One
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0352256,
title = {Textual overlap rather than domain alignment: A comparative study of fine-tuning strategies for specialised machine translation with large language models.},
author = {Yang L and Zhu J and Zhang Z.},
year = {2026},
journal = {PLoS One},
doi = {10.1371/journal.pone.0352256},
url = {https://doi.org/10.1371/journal.pone.0352256}
}RIS
TY - JOUR TI - Textual overlap rather than domain alignment: A comparative study of fine-tuning strategies for specialised machine translation with large language models. AU - Yang L AU - Zhu J AU - Zhang Z. PY - 2026 JO - PLoS One DO - 10.1371/journal.pone.0352256 UR - https://doi.org/10.1371/journal.pone.0352256 ER -
APA
L, Y., J, Z., & Z., Z. (2026). Textual overlap rather than domain alignment: A comparative study of fine-tuning strategies for specialised machine translation with large language models.. PLoS One. https://doi.org/10.1371/journal.pone.0352256
Source records
- europe-pmc · retrieved 2026-09-25T11:21:58.548Z