4 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions?
Weijie Tu, Weijian Deng, Liang Zheng +1
This work aims to develop a measure that can accurately rank the performance of various classifiers when they are tested on unlabeled data from out-of-distribution (OOD) distributi…
cs.CV2024★ 4 cited
A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)
Weijie Tu, Weijian Deng, Tom Gedeon
Contrastive Language-Image Pre-training (CLIP) models have demonstrated remarkable generalization capabilities across multiple challenging distribution shifts. However, there is st…
cs.CV2023★ 3 cited
A Bag-of-Prototypes Representation for Dataset-Level Applications
Weijie Tu, Weijian Deng, Tom Gedeon +1
This work investigates dataset vectorization for two dataset-level tasks: assessing training set suitability and test set difficulty. The former measures how suitable a training se…