10 citations · 11 across the 2 of their papers we have counts for
3 papers
Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu +9
Machine unlearning techniques aim to mitigate unintended memorization in large language models (LLMs). However, existing approaches predominantly focus on the explicit removal of i…
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on Graphs
Hans Hao-Hsun Hsu, Yuesong Shen, Daniel Cremers
Current graph neural networks (GNNs) that tackle node classification on graphs tend to only focus on nodewise scores and are solely evaluated by nodewise metrics. This limits uncer…
What Makes Graph Neural Networks Miscalibrated?
Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani +1
Given the importance of getting calibrated predictions and reliable uncertainty estimations, various post-hoc calibration methods have been developed for neural networks on standar…