SEA-LION: Southeast Asian Languages in One Network
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Abstract (arXiv)
Recently, Large Language Models (LLMs) have dominated much of the artificial intelligence scene with their ability to process and generate natural languages. However, the majority of LLM research and development remains English-centric, leaving low-resource languages such as those in the Southeast Asian (SEA) region under-represented. To address this representation gap, we introduce Llama-SEA-LION-v3-8B-IT and Gemma-SEA-LION-v3-9B-IT, two cutting-edge multilingual LLMs designed for SEA languages. The SEA-LION family of LLMs supports 11 SEA languages, namely English, Chinese, Indonesian, Vietnamese, Malay, Thai, Burmese, Lao, Filipino, Tamil, and Khmer. Our work leverages large-scale multilingual continued pre-training with a comprehensive post-training regime involving multiple stages of instruction fine-tuning, alignment, and model merging. Evaluation results on multilingual benchmarks indicate that our models achieve state-of-the-art performance across LLMs supporting SEA languages. We open-source the models to benefit the wider SEA community.
Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Builds on 38 of its 56 references that are in the map. First posted on arXiv 8 Apr 2025.
Builds on
38 of 56 references.
References · 38
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Citing papers per year: 2025: 4; 2026: 18.
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- 2026Gained in Translation: Privileged Pairwise Judges Enhance Multilingual Reasoning26 Jan 2026
- 2025MERLIN: Multi-Stage Curriculum Alignment for Multilingual Encoder-LLM Integration in Cross-Lingual Reasoning9 Sep 2025
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- 2026Buy versus Build an LLM: A Decision Framework for Governmentscited by 1
- 2026Language-Aware Distillation for Multilingual Instruction-Following Speech LLMs with ASR-Only Supervisioncited by 1
- 2025Sunflower: A New Approach To Expanding Coverage of African Languages in Large Language Modelscited by 0
- 2026HoReN: Normalized Hopfield Retrieval for Large-Scale Sequential Model Editingcited by 0
- 2026Phoenix-VL 1.5 Medium Technical Reportcited by 0
- 2026SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understandingcited by 0
- 2026World Wide Models: Literary Tools for Cultural AIcited by 0
- 2026CultureConverse: A Multilingual Multi-turn Simulation Harness for Culturally Grounded Assistance in East and Southeast Asiacited by 0
- 2026TDR: Tagalog Diacritic Restoration Datasetcited by 0
- 2026SEA-HELM Audio: Evaluating Multilingual ASR-LLM Pipeline Performance Across SEA-HELM Subsetscited by 0
- 2026SEA-HELM Audio: Evaluating Multilingual ASR-LLM Pipeline Performance Across SEA-HELM Subsets14 Oct 2026
- 2026TDR: Tagalog Diacritic Restoration Dataset13 Oct 2026
- 2026CultureConverse: A Multilingual Multi-turn Simulation Harness for Culturally Grounded Assistance in East and Southeast Asia28 Aug 2026
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- 2026SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understanding2 Jun 2026
- 2026Phoenix-VL 1.5 Medium Technical Report11 May 2026
- 2026HoReN: Normalized Hopfield Retrieval for Large-Scale Sequential Model Editing2 May 2026
- 2026Tiny Aya: Bridging Scale and Multilingual Depth12 Mar 2026
- 2026Language-Aware Distillation for Multilingual Instruction-Following Speech LLMs with ASR-Only Supervision7 Mar 2026
- 2026Buy versus Build an LLM: A Decision Framework for Governments13 Feb 2026
- 2025Sunflower: A New Approach To Expanding Coverage of African Languages in Large Language Models8 Oct 2025