#  Introduction   Large language models (LLMs) can feel complicated at first. There are transformers, attention layers, scaling laws, pretraining, instruction tuning, human feedback, retrieval, and many other ideas around them. But the best way to understand large language models is not to start with a huge textbook. A better way is to read a few important papers that each explain one major part of the system . This article is part of a fun series where we learn by exploring core ideas, practical projects, and the research papers behind modern technology. In this article, we will go through five papers that explain how LLMs work . So, let's get started. #  1. Attention Is All You Need   This is the Attention Is All You Need paper that introduced the Transformer architecture , which is the foundation of modern LLMs. Before Transformers, many language models used recurrent or convolutional architectures to process sequences.…