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About this paper
Jinbiao Yang
This research from the Max Planck Institute for Psycholinguistics introduces the Less-is-Better (LiB) model, a cognitively informed tokenizer that applies the 'Principle of Least Effort' to unify subwords, words, and multiword expressions. The LiB model generated 10-15% fewer tokens while maintaining a smaller vocabulary compared to traditional methods, and achieved better compression efficiency.
Key insights
- Applying the cognitive 'Principle of Least Effort' suggests that optimal language processing balances the effort of storing many vocabulary items (types) with the effort of processing many tokens (during comprehension).
- Human brains process language in 'cognitive units' that can be subword, word-level, or multiword expressions, indicating a need for tokenizers to learn units beyond single words.
- Tokenizers should dynamically learn units that approximate human cognitive units, unifying subwords, words, and multiword expressions, to minimize both vocabulary size and token count.
Summary by alphaXiv.
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