most citedMitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates

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cs.CL2026★ 1 cited

Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates

Atsuki Yamaguchi, Terufumi Morishita, Aline Villavicencio +1

Expanding the linguistic diversity of instruct large language models (LLMs) is crucial for global accessibility but is often hindered by the reliance on costly specialized target l…

cs.CL2026

Multi-Model Synthetic Training for Mission-Critical Small Language Models

Nolan Platt, Pragyansmita Nayak

Large Language Models (LLMs) have demonstrated remarkable capabilities across many domains, yet their application to specialized fields remains constrained by the scarcity and comp…