Decoder-Only vs Encoder-Decoder: What Separates Modern Transformers

Decoder-only transformers have become the foundation of contemporary large language models, fundamentally reshaping how AI processes sequential data. Understanding the architectural distinction between masked self-attention and encoder-decoder attention mechanisms is critical for comprehending why most modern LLMs adopt the decoder-only paradigm for superior efficiency and scalability.