XLNet is a state-of-the-art natural language processing model developed to improve upon previous models like BERT. It uses a unique training method called permutation language modeling, which allows it to consider all possible word orders in a sentence. This helps the model understand context better and generate more coherent text. Unlike traditional models that predict the next word based on the previous ones, XLNet captures bidirectional context, meaning it looks at both the left and right sides of a word. This results in improved performance on various language tasks, such as text classification and question answering.