13 citations · 34 across the 8 of their papers we have counts for
8 papers
Inference-Time Rule Eraser: Fair Recognition via Distilling and Removing Biased Rules
Yi Zhang, Dongyuan Lu, Jitao Sang
Machine learning models often make predictions based on biased features such as gender, race, and other social attributes, posing significant fairness risks, especially in societal…
Benign Shortcut for Debiasing: Fair Visual Recognition via Intervention with Shortcut Features
Yi Zhang, Jitao Sang, Junyang Wang +2
Machine learning models often learn to make predictions that rely on sensitive social attributes like gender and race, which poses significant fairness risks, especially in societa…
Zero-shot Image Captioning by Anchor-augmented Vision-Language Space Alignment
Junyang Wang, Yi Zhang, Ming Yan +2
CLIP (Contrastive Language-Image Pre-Training) has shown remarkable zero-shot transfer capabilities in cross-modal correlation tasks such as visual classification and image retriev…
Fair Visual Recognition via Intervention with Proxy Features
Yi Zhang, Jitao Sang, Junyang Wang
Deep learning models often learn to make predictions that rely on sensitive social attributes like gender and race, which poses significant fairness risks, especially in societal a…
FairCLIP: Social Bias Elimination based on Attribute Prototype Learning and Representation Neutralization
Junyang Wang, Yi Zhang, Jitao Sang
The Vision-Language Pre-training (VLP) models like CLIP have gained popularity in recent years. However, many works found that the social biases hidden in CLIP easily manifest in d…
Counterfactually Measuring and Eliminating Social Bias in Vision-Language Pre-training Models
Yi Zhang, Junyang Wang, Jitao Sang
Vision-Language Pre-training (VLP) models have achieved state-of-the-art performance in numerous cross-modal tasks. Since they are optimized to capture the statistical properties o…
Debiasing Backdoor Attack: A Benign Application of Backdoor Attack in Eliminating Data Bias
Shangxi Wu, Qiuyang He, Yi Zhang +1
Backdoor attack is a new AI security risk that has emerged in recent years. Drawing on the previous research of adversarial attack, we argue that the backdoor attack has the potent…
Towards Accuracy-Fairness Paradox: Adversarial Example-based Data Augmentation for Visual Debiasing
Yi Zhang, Jitao Sang
Machine learning fairness concerns about the biases towards certain protected or sensitive group of people when addressing the target tasks. This paper studies the debiasing proble…