Hierarchical Cascaded Tokenization and Dynamic Language State Tracking

This report presents a hardware-aligned tokenization framework that prevents vocabulary explosion without relying on cross-lingual semantic pivots. The framework partitions the token index space into four bounded regions: control identifiers, primitive bytes, surface lexicons, and a universal grapheme pool. Input text is processed through a deterministic three-stage fallback: localized trie prefix matching, canonical graphemic decomposition, and primitive byte mapping. This structure guarantees zero out-of-vocabulary conditions within a compact, hardware-aligned index space. During inference, a finite-state decoder tracks script transitions dynamically to prevent cross-orthographic drift.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-15
DOI
https://doi.org/10.5281/zenodo.22771283
Primary Topic
Natural Language Processing Techniques
Type
article
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article

Hierarchical Cascaded Tokenization and Dynamic Language State Tracking

Young Jin Oh
Zenodo (CERN European Organization for Nuclear Research)
Natural Language Processing Techniques
article

Hierarchical Cascaded Tokenization and Dynamic Language State Tracking

Young Jin Oh
article en

Abstract

This report presents a hardware-aligned tokenization framework that prevents vocabulary explosion without relying on cross-lingual semantic pivots. The framework partitions the token index space into four bounded regions: control identifiers, primitive bytes, surface lexicons, and a universal grapheme pool. Input text is processed through a deterministic three-stage fallback: localized trie prefix matching, canonical graphemic decomposition, and primitive byte mapping. This structure guarantees zero out-of-vocabulary conditions within a compact, hardware-aligned index space. During inference, a finite-state decoder tracks script transitions dynamically to prevent cross-orthographic drift.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 8%
Natural Language Processing Techniques
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