7 citations · 11 across the 4 of their papers we have counts for
4 papers
Modeling the Q-Diversity in a Min-max Play Game for Robust Optimization
Ting Wu, Rui Zheng, Tao Gui +2
Models trained with empirical risk minimization (ERM) are revealed to easily rely on spurious correlations, resulting in poor generalization. Group distributionally robust optimiza…
Enhancing Contrastive Learning with Noise-Guided Attack: Towards Continual Relation Extraction in the Wild
Ting Wu, Jingyi Liu, Rui Zheng +3
The principle of continual relation extraction~(CRE) involves adapting to emerging novel relations while preserving od knowledge. While current endeavors in CRE succeed in preservi…
Less is Better: Recovering Intended-Feature Subspace to Robustify NLU Models
Ting Wu, Tao Gui
Datasets with significant proportions of bias present threats for training a trustworthy model on NLU tasks. Despite yielding great progress, current debiasing methods impose exces…
Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature Perspective
Shihan Dou, Rui Zheng, Ting Wu +5
Natural language understanding (NLU) models tend to rely on spurious correlations (i.e., dataset bias) to achieve high performance on in-distribution datasets but poor performance…