← Search

Ching-Chun Chang

2 accepted papers

2025

Agentic Copyright Watermarking against Adversarial Evidence Forgery with Purification-Agnostic Curriculum Proxy Learning

ICASSP 2025accepted

With the proliferation of AI agents in various domains, protecting the ownership of AI models has become crucial due to the significant investment in their development. Unauthorized use and illegal distribution of these models pose serious threats to intellectual property, necessitating effective co…

Cited by 0SourceScholar
2025

Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off

ICLR 2025poster

Adversarial training often suffers from a robustness-accuracy trade-off, where achieving high robustness comes at the cost of accuracy. One approach to mitigate this trade-off is leveraging invariance regularization, which encourages model invariance under adversarial perturbations; however, it stil…

Cited by 0SourcePDFScholar