BERT, RoBERTa, and XLNet are all state-of-the-art transformer-based models for natural language processing. The key differences are that BERT uses masked language modeling and next sentence prediction, RoBERTa extends BERT with additional training data and longer training time, and XLNet introduces a permutation-based approach that allows for bidirectional context while maintaining the ability to model dependencies between all positions.