· Xiaojing Yang · NLP and LLMs
Transformers for NLP
How Transformers combine self-attention, feed-forward layers, residuals, and positional information.
Blog
Foundations and research notes on mathematics, statistics, machine learning, NLP, LLMs, model evaluation, and applied AI systems.
- · Xiaojing Yang · Statistics
Why Statistics Matters for AI Research
Statistics is not just a set of formulas. It is a way to reason about uncertainty, evidence, and trust in AI experiments.
- · Xiaojing Yang · NLP and LLMs
Word Embeddings and Sentence Embeddings
How discrete language becomes vector space, and why sentence embeddings matter for retrieval and evaluation.
- · Xiaojing Yang · Statistics
用于多模型比较的 ANOVA
ANOVA 问的是：组间差异是否大于组内噪声。
- · Xiaojing Yang · NLP and LLMs
Attention Mechanism：注意力机制
注意力机制是一种学习到的上下文选择方式：每个 token 应该看哪里。
- · Xiaojing Yang · Statistics
Bias–Variance Trade-off
偏差和方差解释了为什么模型太简单或太灵活都会失败。