6 citations · 7 across the 7 of their papers we have counts for
7 papers
De-attribute to Forget for LLM Unlearning
Xinyang Lu, Jiabao Pan, Rachael Hwee Ling Sim +3
The rapid development of large language models (LLMs) has raised concerns on the use of inappropriate data for training, which has led to a growing interest in LLM unlearning. Many…
WaterDrum: Watermarking for Data-centric Unlearning Metric
Xinyang Lu, Xinyuan Niu, Gregory Kang Ruey Lau +7
Large language model (LLM) unlearning is critical in real-world applications where it is necessary to efficiently remove the influence of private, copyrighted, or harmful data from…
DUPRE: Data Utility Prediction for Efficient Data Valuation
Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Quoc Phong Nguyen +2
Data valuation is increasingly used in machine learning (ML) to decide the fair compensation for data owners and identify valuable or harmful data for improving ML models. Cooperat…
Confidence Elicitation: A New Attack Vector for Large Language Models
Brian Formento, Chuan Sheng Foo, See-Kiong Ng
A fundamental issue in deep learning has been adversarial robustness. As these systems have scaled, such issues have persisted. Currently, large language models (LLMs) with billion…
TRACE: TRansformer-based Attribution using Contrastive Embeddings in LLMs
Cheng Wang, Xinyang Lu, See-Kiong Ng +1
The rapid evolution of large language models (LLMs) represents a substantial leap forward in natural language understanding and generation. However, alongside these advancements co…
On Newton's Method to Unlearn Neural Networks
Nhung Bui, Xinyang Lu, Rachael Hwee Ling Sim +2
With the widespread applications of neural networks (NNs) trained on personal data, machine unlearning has become increasingly important for enabling individuals to exercise their…
PINNACLE: PINN Adaptive ColLocation and Experimental points selection
Gregory Kang Ruey Lau, Apivich Hemachandra, See-Kiong Ng +1
Physics-Informed Neural Networks (PINNs), which incorporate PDEs as soft constraints, train with a composite loss function that contains multiple training point types: different ty…