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Sanskrit tokenization penalty higher than English, study finds

By PulseAugur Editorial · [1 sources] ·

A new research paper investigates the tokenization efficiency of Sanskrit compared to English and Hindi when processed by modern language models. The study found that Sanskrit requires significantly more tokens per unit of meaning than English, particularly when using deployed tokenizers with large vocabularies. However, the tokenization penalty decreases when comparing Sanskrit to Hindi, and the gap narrows further with larger vocabulary sizes. The research suggests that while Sanskrit is information-dense per word, its complex morphology leads to a higher token count per proposition in practical applications. AI

IMPACT Highlights potential inefficiencies in processing information-dense languages like Sanskrit with current LLM tokenization methods.

RANK_REASON Research paper analyzing tokenization efficiency of Sanskrit. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Sanskrit tokenization penalty higher than English, study finds

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Research paper analyzing tokenization efficiency of Sanskrit. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Devansh Sharma ·

    Fewer Words, Not Fewer Tokens: Measuring the Sanskrit Tokenization Penalty per Proposition

    arXiv:2609.12960v1 Announce Type: new Abstract: Sanskrit fuses case, number, person and tense into word endings and chains clauses into compounds, so it is information-dense per word. Whether that density survives subword tokenization is a separate question, to be asked per unit …

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