Dynamic BPE: Adaptive tokenization for pre-training and fine-tuning. Balances flexibility and consistency.

BPE Dropout: Stochastic subword segmentation. Applies dropout to merges during tokenization. Improves model robustness and generalization.

Word Piece Tokenization: Subword segmentation for NLP. Builds vocab from frequent subwords & handles rare words