3 papers
cs.CV2025
Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability
Zhiyu Zhu, Zhibo Jin, Jiayu Zhang +4
The task of identifying multimodal image-text representations has garnered increasing attention, particularly with models such as CLIP (Contrastive Language-Image Pretraining), whi…
cs.AI2024
Attribution for Enhanced Explanation with Transferable Adversarial eXploration
Zhiyu Zhu, Jiayu Zhang, Zhibo Jin +3
The interpretability of deep neural networks is crucial for understanding model decisions in various applications, including computer vision. AttEXplore++, an advanced framework bu…
cs.AI2024
Enhancing Transferability of Adversarial Attacks with GE-AdvGAN+: A Comprehensive Framework for Gradient Editing
Zhibo Jin, Jiayu Zhang, Zhiyu Zhu +4
Transferable adversarial attacks pose significant threats to deep neural networks, particularly in black-box scenarios where internal model information is inaccessible. Studying ad…