Layering Attention: How Transformers Capture Complex Relationships

This article explains a fundamental mechanism behind modern language models—how stacking multiple self-attention layers enables transformers to progressively understand complex relationships between words. Understanding this architecture is essential for anyone building or deploying transformer-based AI systems, as it directly determines the model's capability to handle nuanced context and semantic meaning.