TRANSMI: A Framework to Create Strong Baselines from Multilingual Pretrained Language Models for Transliterated Data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AIK7NAQMU" target="_blank" >RIV/00216208:11320/26:IK7NAQMU - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

TRANSMI: A Framework to Create Strong Baselines from Multilingual Pretrained Language Models for Transliterated Data

Original language description

Transliterating related languages that use different scripts into a common script is effective for improving crosslingual transfer in downstream tasks. However, this methodology often makes pretraining a model from scratch unavoidable, as transliteration brings about new subwords not covered in existing multilingual pretrained language models (mPLMs). This is undesirable because it requires a large computation budget. A more promising way is to make full use of available mPLMs. To this end, this paper proposes a simple but effective framework: Transliterate-Merge-Initialize (TRANSMI). TRANSMI can create strong baselines for data that is transliterated into a common script by exploiting an existing mPLM and its tokenizer without any training. TRANSMI has three stages: (a) transliterate the vocabulary of an mPLM into a common script; (b) merge the new vocabulary with the original vocabulary; and (c) initialize the embeddings of the new subwords. We apply TRANSMI to three strong recent mPLMs. Our experiments demonstrate that TRANSMI not only preserves the mPLM's ability to handle non-transliterated data, but also enables it to effectively process transliterated data, thereby facilitating crosslingual transfer across scripts. The results show consistent improvements of 3% to 34% for different mPLMs and tasks. We make our code and models publicly available at https://github.com/cisnlp/TransMI. © 2025 Association for Computational Linguistics.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proc. Main Conf. Int. Conf. Comput. Linguist., COLING

ISBN

979-8-89176-196-4

ISSN

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e-ISSN

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Number of pages

27

Pages from-to

469-495

Publisher name

Association for Computational Linguistics (ACL)

Place of publication

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Event location

Abu Dhabi

Event date

Jan 1, 2026

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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