6 citations · 20 across the 12 of their papers we have counts for
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cs.CL2025
Safety-Aligned Weights Are Not Enough: Refusal-Teacher-Guided Finetuning Enhances Safety and Downstream Performance under Harmful Finetuning Attacks
Seokil Ham, Yubin Choi, Yujin Yang +3
While Finetuning-as-a-Service (FaaS) enables customization of Large Language Models (LLMs) using user data, this service is vulnerable to safety degradation when user data includes…
cs.CV2025
Long-tailed Adversarial Training with Self-Distillation
Seungju Cho, Hongsin Lee, Changick Kim
Adversarial training significantly enhances adversarial robustness, yet superior performance is predominantly achieved on balanced datasets. Addressing adversarial robustness in th…