168 citations · 224 across the 11 of their papers we have counts for
11 papers
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…
Evaluation and Analysis of Hallucination in Large Vision-Language Models
Junyang Wang, Yiyang Zhou, Guohai Xu +9
Large Vision-Language Models (LVLMs) have recently achieved remarkable success. However, LVLMs are still plagued by the hallucination problem, which limits the practicality in many…
From Association to Generation: Text-only Captioning by Unsupervised Cross-modal Mapping
Junyang Wang, Ming Yan, Yi Zhang +1
With the development of Vision-Language Pre-training Models (VLPMs) represented by CLIP and ALIGN, significant breakthroughs have been achieved for association-based visual tasks s…
mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality
Qinghao Ye, Haiyang Xu, Guohai Xu +15
Large language models (LLMs) have demonstrated impressive zero-shot abilities on a variety of open-ended tasks, while recent research has also explored the use of LLMs for multi-mo…
Improved Visual Fine-tuning with Natural Language Supervision
Junyang Wang, Yuanhong Xu, Juhua Hu +3
Fine-tuning a visual pre-trained model can leverage the semantic information from large-scale pre-training data and mitigate the over-fitting problem on downstream vision tasks wit…
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…
Piecewise Linear Patch Reconstruction for Segmentation and Description of Non-smooth Image Structures
Junyan Wang, Kap Luk Chan
In this paper, we propose a unified energy minimization model for the segmentation of non-smooth image structures. The energy of piecewise linear patch reconstruction is considered…
Active Contour with A Tangential Component
Junyan Wang, Kap Luk Chan
Conventional edge-based active contours often require the normal component of an edge indicator function on the optimal contours to approximate zero, while the tangential component…