· Xiaojing Yang · Multilingual AI
Data Scaling for LoRA Domain Adaptation
A research note on how to study the effect of domain data size in LoRA-based machine translation adaptation.
A research note on how to study the effect of domain data size in LoRA-based machine translation adaptation.
A research-story version of my LoRA NMT project: problem framing, data, method, evaluation, findings, limitations, and future work.
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.
如何研究领域数据规模对 LoRA 机器翻译适配的影响:数据多少才够,什么时候收益递减,什么时候是数据质量问题。
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。
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。