· 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.
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.
A research-oriented guide to training-data attribution: attribution units, utility functions, Shapley values, influence methods, causality, scalability, and uncertainty.