SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models
  for Southeast Asian Languages
Large Language Models (LLMs) have shown remarkable abilities across various
tasks, yet their development has predominantly centered on high-resource
languages like English and Chinese, leaving low-resource languages underserved.
To address this disparity, we present SeaLLMs 3, the latest iteration of the
SeaLLMs model family, tailored for Southeast Asian languages. This region,
characterized by its rich linguistic diversity, has lacked adequate language
technology support. SeaLLMs 3 aims to bridge this gap by covering a
comprehensive range of languages spoken in this region, including English,
Chinese, Indonesian, Vietnamese, Thai, Tagalog, Malay, Burmese, Khmer, Lao,
Tamil, and Javanese. Leveraging efficient language enhancement techniques and a
specially constructed instruction tuning dataset, SeaLLMs 3 significantly
reduces training costs while maintaining high performance and versatility. Our
model excels in tasks such as world knowledge, mathematical reasoning,
translation, and instruction following, achieving state-of-the-art performance
among similarly sized models. Additionally, we prioritized safety and
reliability by addressing both general and culture-specific considerations and
incorporated mechanisms to reduce hallucinations. This work underscores the
importance of inclusive AI, showing that advanced LLM capabilities can benefit
underserved linguistic and cultural communities.
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Yiran Zhao
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Mahani Aljunied
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Chaoqun Liu
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CHAOQUN LIU
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Yue Deng
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Weiwen Xu
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Xu Weiwen
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Yew Ken Chia
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Xin Li
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Xin Li
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Lidong Bing
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SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models
  for Southeast Asian Languages
Large Language Models (LLMs) have shown remarkable abilities across various
tasks, yet their development has predominantly centered on high-resource
languages like English and Chinese, leaving low-resource languages underserved.
To address this disparity, we present SeaLLMs 3, the latest iteration of the
SeaLLMs model family, tailored for Southeast Asian languages. This region,
characterized by its rich linguistic diversity, has lacked adequate language
technology support. SeaLLMs 3 aims to bridge this gap by covering a
comprehensive range of languages spoken in this region, including English,
Chinese, Indonesian, Vietnamese, Thai, Tagalog, Malay, Burmese, Khmer, Lao,
Tamil, and Javanese. Leveraging efficient language enhancement techniques and a
specially constructed instruction tuning dataset, SeaLLMs 3 significantly
reduces training costs while maintaining high performance and versatility. Our
model excels in tasks such as world knowledge, mathematical reasoning,
translation, and instruction following, achieving state-of-the-art performance
among similarly sized models. Additionally, we prioritized safety and
reliability by addressing both general and culture-specific considerations and
incorporated mechanisms to reduce hallucinations. This work underscores the
importance of inclusive AI, showing that advanced LLM capabilities can benefit
underserved linguistic and cultural communities.
SeaLLMs 3 is a large language model optimized for Southeast Asian languages, offering state-of-the-art performance in various tasks while addressing safety and cultural considerations.
large language models SeaLLMs linguistic diversity language enhancement instruction tuning world knowledge mathematical reasoning translation instruction following hallucinations inclusive AI