6 citations · 16 across the 13 of their papers we have counts for
5 papers · 1 filter
BADTV: Unveiling Backdoor Threats in Third-Party Task Vectors
Chia-Yi Hsu, Yu-Lin Tsai, Yu Zhe +6
Task arithmetic in large-scale pre-trained models enables agile adaptation to diverse downstream tasks without extensive retraining. By leveraging task vectors (TVs), users can per…
Safe LoRA: the Silver Lining of Reducing Safety Risks when Fine-tuning Large Language Models
Chia-Yi Hsu, Yu-Lin Tsai, Chih-Hsun Lin +3
While large language models (LLMs) such as Llama-2 or GPT-4 have shown impressive zero-shot performance, fine-tuning is still necessary to enhance their performance for customized…
Ring-A-Bell! How Reliable are Concept Removal Methods for Diffusion Models?
Yu-Lin Tsai, Chia-Yi Hsu, Chulin Xie +6
Diffusion models for text-to-image (T2I) synthesis, such as Stable Diffusion (SD), have recently demonstrated exceptional capabilities for generating high-quality content. However,…
Formalizing Generalization and Robustness of Neural Networks to Weight Perturbations
Yu-Lin Tsai, Chia-Yi Hsu, Chia-Mu Yu +1
Studying the sensitivity of weight perturbation in neural networks and its impacts on model performance, including generalization and robustness, is an active research topic due to…
Non-Singular Adversarial Robustness of Neural Networks
Yu-Lin Tsai, Chia-Yi Hsu, Chia-Mu Yu +1
Adversarial robustness has become an emerging challenge for neural network owing to its over-sensitivity to small input perturbations. While being critical, we argue that solving t…