Byte Pair Encoding (BPE) is a subword tokenization method that merges the most frequent pairs of characters or subwords. It creates a fixed-size vocabulary of subword units. In the article's context, BPE is often used to prepare input sequences for self-attention layers. This helps manage rare or unknown words and keeps sequence lengths reasonable. BPE enables Transformers to generalize across morphology and misspellings. It's widely used in models like GPT and BERT. Understanding BPE clarifies how raw text becomes model-ready input.