SuperBPE: Advancing Language Models with Cross-Word Tokenization

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SuperBPE is a new tokenization algorithm developed by researchers from the University of Washington, NVIDIA, and the Allen Institute for AI. It enhances the popular byte-pair encoding (BPE) algorithm by incorporating superword tokens that span multiple words, improving encoding efficiency. SuperBPE outperforms the traditional BPE baseline across various benchmarks and tasks, including knowledge, reasoning, coding, and reading comprehension, without requiring changes to the underlying model architecture. The approach offers substantial performance gains and reduced computational costs for language models.