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Chih-Hsun Lin

3 accepted papers

2025

VP-NTK: Exploring the Benefits of Visual Prompting in Differentially Private Data Synthesis

ICASSP 2025accepted

Differentially private (DP) synthetic data has become the de facto standard for releasing sensitive data. However, many DP generative models suffer from the low utility of synthetic data, especially for high-resolution images. On the other hand, one of the emerging techniques in parameter efficient…

Cited by 0SourceScholar
2024

Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models?

ICLR 2024poster

Diffusion models for text-to-image (T2I) synthesis, such as Stable Diffusion (SD), have recently demonstrated exceptional capabilities for generating high-quality content. However, this progress has raised several concerns of potential misuse, particularly in creating copyrighted, prohibited, and re…

2024

Safe LoRA: The Silver Lining of Reducing Safety Risks when Finetuning Large Language Models

NeurIPS 2024poster

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 datasets, domain-specific tasks, or other private needs. However, fine-tuning all parameters of LLMs requires significan…