26 citations · 42 across the 19 of their papers we have counts for
19 papers
Uncertainty-Aware Metabolic Stability Prediction with Dual-View Contrastive Learning
Peijin Guo, Minghui Li, Hewen Pan +6
Accurate prediction of molecular metabolic stability (MS) is critical for drug research and development but remains challenging due to the complex interplay of molecular interactio…
Spa-VLM: Stealthy Poisoning Attacks on RAG-based VLM
Lei Yu, Yechao Zhang, Ziqi Zhou +6
With the rapid development of the Vision-Language Model (VLM), significant progress has been made in Visual Question Answering (VQA) tasks. However, existing VLM often generate ina…
Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets
Yechao Zhang, Yuxuan Zhou, Tianyu Li +4
Transfer learning from pre-trained encoders has become essential in modern machine learning, enabling efficient model adaptation across diverse tasks. However, this combination of…
Improving Generalization of Universal Adversarial Perturbation via Dynamic Maximin Optimization
Yechao Zhang, Yingzhe Xu, Junyu Shi +4
Deep neural networks (DNNs) are susceptible to universal adversarial perturbations (UAPs). These perturbations are meticulously designed to fool the target model universally across…
Exploring Gradient-Guided Masked Language Model to Detect Textual Adversarial Attacks
Xiaomei Zhang, Zhaoxi Zhang, Yanjun Zhang +4
Textual adversarial examples pose serious threats to the reliability of natural language processing systems. Recent studies suggest that adversarial examples tend to deviate from t…
Multi-Modality Representation Learning for Antibody-Antigen Interactions Prediction
Peijin Guo, Minghui Li, Hewen Pan +6
While deep learning models play a crucial role in predicting antibody-antigen interactions (AAI), the scarcity of publicly available sequence-structure pairings constrains their ge…