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MERaLiON-TextLLM: Cross-Lingual Understanding of Large Language Models in Chinese, Indonesian, Malay, and Singlish

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arxiv 2501.08335 v3 pith:6U62F2PG submitted 2024-12-21 cs.CL cs.AI

classification cs.CLcs.AI
keywords languagemodelsunderstandingacrosscapabilitieschinesecross-lingualindonesian
verification ladder T0 review T1 audit T2 compute T3 formal
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Multilingual large language models (MLLMs) have shown impressive capabilities across a variety of languages. However, efficacy can differ greatly between different language families, especially for those with limited linguistic resources. This report presents MERaLiON-TextLLM, a series of open-source language models specifically tailored to improve understanding and generation in Chinese, Indonesian, Malay, and Singlish. The initial released model is built on Llama-3-8B-Base and refined through a meticulously crafted process of continued pre-training and weight merging. Our approach achieves performance improvements across benchmarks in these languages, exceeding the capabilities of the official Llama-3 models. We provide the model checkpoints as a resource to support further research and development in cross-lingual language understanding.

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Cited by 1 Pith paper

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

  1. The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It

    cs.CL 2025-05 accept novelty 6.0 of 10

    LLM safety research at ACL venues from 2020 to 2024 is predominantly English-only, and the language gap is growing over time.

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