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Boundless Byte Pair Encoding: Breaking the Pre-tokenization Barrier

Published: March 31, 2025 | arXiv ID: 2504.00178v1

By: Craig W. Schmidt , Varshini Reddy , Chris Tanner and more

Potential Business Impact:

Makes computers understand words better by merging them.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

Pre-tokenization, the initial step in many modern tokenization pipelines, segments text into smaller units called pretokens, typically splitting on whitespace and punctuation. While this process encourages having full, individual words as tokens, it introduces a fundamental limitation in most tokenization algorithms such as Byte Pair Encoding (BPE). Specifically, pre-tokenization causes the distribution of tokens in a corpus to heavily skew towards common, full-length words. This skewed distribution limits the benefits of expanding to larger vocabularies, since the additional tokens appear with progressively lower counts. To overcome this barrier, we propose BoundlessBPE, a modified BPE algorithm that relaxes the pretoken boundary constraint. Our approach selectively merges two complete pretokens into a larger unit we term a superword. Superwords are not necessarily semantically cohesive. For example, the pretokens " of" and " the" might be combined to form the superword " of the". This merging strategy results in a substantially more uniform distribution of tokens across a corpus than standard BPE, and compresses text more effectively, with an approximate 20% increase in bytes per token.

Country of Origin
🇮🇱 Israel

Repos / Data Links

Page Count
18 pages

Category
Computer Science:
Computation and Language