12 citations · 21 across the 13 of their papers we have counts for
4 papers · 1 filter
Proximity-Informed Calibration for Deep Neural Networks
Miao Xiong, Ailin Deng, Pang Wei Koh +4
Confidence calibration is central to providing accurate and interpretable uncertainty estimates, especially under safety-critical scenarios. However, we find that existing calibrat…
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks
Yuwen Li, Miao Xiong, Bryan Hooi
Label errors have been found to be prevalent in popular text, vision, and audio datasets, which heavily influence the safe development and evaluation of machine learning algorithms…
Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement
Ailin Deng, Miao Xiong, Bryan Hooi
Reliable application of machine learning is of primary importance to the practical deployment of deep learning methods. A fundamental challenge is that models are often unreliable…
Trust, but Verify: Using Self-Supervised Probing to Improve Trustworthiness
Ailin Deng, Shen Li, Miao Xiong +2
Trustworthy machine learning is of primary importance to the practical deployment of deep learning models. While state-of-the-art models achieve astonishingly good performance in t…