SSU mitigates catastrophic forgetting in low-resource LLM target-language adaptation by scoring and column-wise freezing source-critical parameters, reducing source degradation to ~3% versus ~20% for full fine-tuning while matching target performance.
Mitigating catastrophic forgetting in language transfer via model merging
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Jupiter-N is a post-trained version of Nemotron 3 Super that reports gains on Welsh benchmarks, terminal agent tasks, and instruction following while retaining base capabilities, released openly as a template for sovereign cultural AI adaptation.
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Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates
SSU mitigates catastrophic forgetting in low-resource LLM target-language adaptation by scoring and column-wise freezing source-critical parameters, reducing source degradation to ~3% versus ~20% for full fine-tuning while matching target performance.