Llms

Sparse vs. Dense Attention: How Transformers Trade Cost for Context

Dense attention offers complete context but incurs quadratic computational cost, while sparse attention reduces this by restricting token interactions, enabling longer sequences. The choice between them is a trade-off between efficiency and expressiveness, driven by sequence length and task needs.