Architecture
XLNet is a generalized autoregressive pretraining model that combines the advantages of autoregressive (AR) language modeling and autoencoding (AE) while avoiding the shortcomings of both. It introduces permutation-based language modeling, allowing the model to predict tokens in all possible orders rather than in a fixed sequence. This approach enables XLNet to capture bidirectional context effectively. Additionally, XLNet integrates ideas from Transformer-XL, incorporating a two-stream self-attention mechanism to handle long-range dependencies and improve performance on various NLP tasks.