15 citations · 17 across the 11 of their papers we have counts for
5 papers · 1 filter
SAGE: Spuriousness-Aware Guided Prompt Exploration for Mitigating Multimodal Bias
Wenqian Ye, Di Wang, Guangtao Zheng +2
Large vision-language models, such as CLIP, have shown strong zero-shot classification performance by aligning images and text in a shared embedding space. However, CLIP models oft…
Benchmarking Spurious Bias in Few-Shot Image Classifiers
Guangtao Zheng, Wenqian Ye, Aidong Zhang
Few-shot image classifiers are designed to recognize and classify new data with minimal supervision and limited data but often show reliance on spurious correlations between classe…
Spuriousness-Aware Meta-Learning for Learning Robust Classifiers
Guangtao Zheng, Wenqian Ye, Aidong Zhang
Spurious correlations are brittle associations between certain attributes of inputs and target variables, such as the correlation between an image background and an object class. D…
MM-SpuBench: Towards Better Understanding of Spurious Biases in Multimodal LLMs
Wenqian Ye, Bohan Liu, Guangtao Zheng +6
Spurious bias, a tendency to exploit spurious correlations between superficial input attributes and prediction targets, has revealed a severe robustness pitfall in classical machin…
AdvST: Revisiting Data Augmentations for Single Domain Generalization
Guangtao Zheng, Mengdi Huai, Aidong Zhang
Single domain generalization (SDG) aims to train a robust model against unknown target domain shifts using data from a single source domain. Data augmentation has been proven an ef…