4 papers
Rendering Data Unlearnable by Exploiting LLM Alignment Mechanisms
Ruihan Zhang, Jun Sun
Large language models (LLMs) are increasingly trained on massive, heterogeneous text corpora, raising serious concerns about the unauthorised use of proprietary or personal data du…
Towards Provably Unlearnable Examples via Bayes Error Optimisation
Ruihan Zhang, Jun Sun, Ee-Peng Lim +1
The recent success of machine learning models, especially large-scale classifiers and language models, relies heavily on training with massive data. These data are often collected…
Correct-By-Construction: Certified Individual Fairness through Neural Network Training
Ruihan Zhang, Jun Sun
Fairness in machine learning is more important than ever as ethical concerns continue to grow. Individual fairness demands that individuals differing only in sensitive attributes r…
A Test Suite for Efficient Robustness Evaluation of Face Recognition Systems
Ruihan Zhang, Jun Sun
Face recognition is a widely used authentication technology in practice, where robustness is required. It is thus essential to have an efficient and easy-to-use method for evaluati…