Funding: This work was supported by “the Fundamental Research Funds for the Central Universities” (25CAFUC03077).
References
Doğru, G. (2024). Creating domain-specific translation memories for machine translation fine-tuning. Tradumàtica, (22), 1-30.
Elshin, D., Karpachev, N., Gruzdev, B., Golovanov, I., Ivanov, G., Antonov, A., ... & Denisov, K. (2024, November). From general LLM to translation: How we dramatically improve translation quality using human evaluation data for LLM finetuning. In Proceedings of the Ninth Conference on Machine Translation (pp. 247-252).
Giampieri, P. (2023). Is machine translation reliable in the legal field? A corpus-based critical comparative analysis for teaching ESP at tertiary level. ESP Today, 11(1), 119-137.
Gilchenko, R. A. (2005). The interrelation between the adequacy of aviation terms translation and safety of flights. Bulletin of the National Aviation University, 2(24), 184-188.
Lyu, C., Xu, J., & Wang, L. (2023). New trends in machine translation using large language models: Case examples with ChatGPT. arXiv preprintarXiv:2305.01181.
Mukherjee, A., & Shrivastava, M. (2025). Lost in translation? Found in evaluation: A comprehensive survey on sentence-level translation evaluation. ACM Computing Surveys.
Paletayeva, V., & Zubtsou, I. Professional English Aviation Terms: Usage and Translation. In The XI International Science Conference “Implementation of modern science in practice”, November 29-December 01, San Francisco, USA. 504 p. (p. 441).
Rivera-Trigueros, I. (2022). Machine translation systems and quality assessment: A systematic review. Language Resources and Evaluation, 56(2), 593-619.
Turian, J. P., Shea, L., & Melamed, I. D. (2006). Evaluation of machine translation and its evaluation. Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers, 205-208.
Wang, A., Lin, M., & Tognolini, J. (n.d.). A new model for assessing civil aviation translation quality: Civil Aviation Translation Quality Assessment Model. Available at SSRN 5056637.
Wang, H., Wu, H., He, Z., Huang, L., & Church, K. W. (2022). Progress in machine translation. Engineering, 18, 143-153.
Wu, T., He, S., Liu, J., Sun, S., Liu, K., Han, Q. L., & Tang, Y. (2023). A brief overview of ChatGPT: The history, status quo and potential future development. IEEE/CAA Journal of Automatica Sinica, 10(5), 1122-1136.
Zheng, J., Hong, H., Liu, F., Wang, X., Su, J., Liang, Y., & Wu, S. (2024). Fine-tuning large language models for domain-specific machine translation. arXiv preprintarXiv:2402.15061.