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MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling

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arxiv 2403.10691 v2 pith:OQK2PIPX submitted 2024-03-15 cs.CL cs.AIcs.LG

classification cs.CLcs.AIcs.LG
keywords languagesdiverseencodingmultilingualmyteacrosslanguagemethods
verification ladder T0 review T1 audit T2 compute T3 formal
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A major consideration in multilingual language modeling is how to best represent languages with diverse vocabularies and scripts. Although contemporary text encoding methods cover most of the world's writing systems, they exhibit bias towards the high-resource languages of the Global West. As a result, texts of underrepresented languages tend to be segmented into long sequences of linguistically meaningless units. To address the disparities, we introduce a new paradigm that encodes the same information with segments of consistent size across diverse languages. Our encoding convention (MYTE) is based on morphemes, as their inventories are more balanced across languages than characters, which are used in previous methods. We show that MYTE produces shorter encodings for all 99 analyzed languages, with the most notable improvements for non-European languages and non-Latin scripts. This, in turn, improves multilingual LM performance and diminishes the perplexity gap throughout diverse languages.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models

    cs.CL 2026-05 conditional novelty 7.0 of 10

    Scratchpad Patching decouples compute from patch size in byte-level language models by inserting entropy-triggered scratchpads to update patch context dynamically.

  2. The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices?

    cs.CL 2026-01 accept novelty 4.0 of 10

    Performance gaps in multilingual LMs frequently arise from modeling choices such as tokenization and data exposure rather than intrinsic linguistic complexity.

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