most citedSemantic-Anchored, Class Variance-Optimized Clustering for Robust Semi-Supervised Few-Shot Learning

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cs.CL2026

Learning to Stay Safe: Adaptive Regularization Against Safety Degradation during Fine-Tuning

Jyotin Goel, Souvik Maji, Pratik Mazumder

Instruction-following language models are trained to be helpful and safe, yet their safety behavior can deteriorate under benign fine-tuning and worsen under adversarial updates. E…