Tag: Domain Adaptation

A research-story version of my LoRA NMT project: problem framing, data, method, evaluation, findings, limitations, and future work.

Why terminology should be evaluated explicitly in domain machine translation, especially when automatic metrics can hide critical technical errors.

A research-facing explanation of why LoRA is a good fit for low-resource domain machine translation: controlled adaptation, lower experimental cost, and reduced overfitting risk.

用研究叙事方式解释我的 LoRA NMT 项目：问题定义、数据、方法、评估、发现、局限与未来工作。

为什么领域机器翻译必须单独评估术语，尤其是在自动指标可能掩盖关键技术错误的时候。

从研究角度解释为什么 LoRA 适合低资源领域机器翻译：受控适配、更低实验成本，以及较低过拟合风险。