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This report details the release of Nemotron-SEA-LION-v4.8, a specialized large language model family designed to enhance performance in seven Southeast Asian languages through continued pretraining and distillation techniques. The technical analysis highlights significant improvements in instruction following and reasoning capabilities across these specific linguistic contexts, leveraging NVIDIA's Nemotron 3 architecture as its foundation.
SEA-LION-v4.8: A Technical Report
arXiv:2609.18310v1 Announce Type: new Abstract: We introduce Nemotron-SEA-LION-v4.8, a family of Southeast Asian Languages in One Network (SEA-LION) built upon NVIDIA Nemotron 3. The family includes 30B-A3B and 120B-A12B models, with both continued-pretrained base checkpoints and post-trained variants. We adapt the models using Southeast Asian, reasoning, code, and multilingual parallel datasets, followed by post-training with supervised fine-tuning and online on-policy distillation. On SEA-HELM, the 30B-A3B model improves the overall SEA score from 46.06 to 51.57, while the 120B-A12B model improves from 49.30 to 63.44. The strongest gains are observed in instruction following, natural language reasoning, and natural language understanding across seven Southeast Asian languages.
Title:SEA-LION-v4.8: A Technical Report
Abstract:We introduce Nemotron-SEA-LION-v4.8, a family of Southeast Asian Languages in One Network (SEA-LION) built upon NVIDIA Nemotron 3. The family includes 30B-A3B and 120B-A12B models, with both continued-pretrained base checkpoints and post-trained variants. We adapt the models using Southeast Asian, reasoning, code, and multilingual parallel datasets, followed by post-training with supervised fine-tuning and online on-policy distillation. On SEA-HELM, the 30B-A3B model improves the overall SEA score from 46.06 to 51.57, while the 120B-A12B model improves from 49.30 to 63.44. The strongest gains are observed in instruction following, natural language reasoning, and natural language understanding across seven Southeast Asian languages.
Computation and Language (cs.CL)
arXiv:2609.18310 [cs.CL]
(or arXiv:2609.18310v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2609.18310 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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