How Far Should Tokenization Go? Predictive Effectiveness and Relational Losslessness
GPT-style models have achieved remarkable success with finite vocabularies of reusable tokens, making the token interface a central component of modern sequence modeling. Symbolic music appears naturally compatible with this paradigm: it consists of discrete note events and recurring structures such as chords, motifs, and phrases. However, when tokenization moves beyond language, the interface must be specified for each domain. Existing work offers many effective designs, but no unified criterion for deciding what tokenization should represent and how far it should go. Using predictive codelength as a common criterion, we formulate the Effectiveness--Losslessness Framework to define where...
| Authors | Yi Wang |
|---|---|
| Primary category | cs.LG |
| Published | 18 August 2026 |
| Last updated at source | 28 August 2026 |
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