· Xiaojing Yang · Model Evaluation
领域 MT 中的术语评估问题
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。
Tag: Machine Translation
- · Xiaojing Yang · Multilingual AI
为什么 LoRA 适合低资源领域适配
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。
- · Xiaojing Yang · Explainability and Responsible AI
Training Data Attribution for NLP Research
A research-oriented guide to training-data attribution: attribution units, utility functions, Shapley values, influence methods, causality, scalability, and uncertainty.
- · Xiaojing Yang · Explainability and Responsible AI
NLP 研究中的 Training Data Attribution
一篇面向研究和面试的 training-data attribution 笔记：归因单位、utility function、Shapley value、influence methods、因果性、可扩展性和不确定性。
- · Xiaojing Yang · Multilingual AI
Why Low-Resource Domain MT Is Hard
Domain-specific machine translation is not only a modeling problem. It is a data, terminology, evaluation, and risk problem.
- · Xiaojing Yang · NLP & LLMs
LoRA for Neural Machine Translation
A practical explanation of LoRA for NMT: what it changes, why it is useful for domain adaptation, and how it differs from full fine-tuning.