A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. The largest and most capable LLMs are generative pretrained transformers (GPTs). Modern models can be fine-tuned for specific tasks or guided by prompt engineering. These models acquire predictive power regarding syntax, semantics, and ontologies inherent in human language corpora, but they also inherit inaccuracies and biases present in the data they are trained in.

In the present book, twelve typical literatures about Large Language Model published on international authoritative journals were selected to introduce the worldwide newest progress, which contains reviews or original researches on Large Language Model. We hope this book can demonstrate advances in Large Language Model as well as give references to the researchers, students and other related people.