Papers by Ali Nazari
MorphBPE: Morphology-Aware Tokenization for Efficient LLM Training (2026.findings-acl)
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| Challenge: | Tokenization is a key design choice in modern NLP systems and a critical bottleneck for multilingual Large Language Models. |
| Approach: | They propose a tokenization extension that constrains merge operations to respect morpheme boundaries while preserving inference. |
| Outcome: | The proposed tokenization improves morphological coherence and language model cross-entropy in four languages. |