Defending Evasion Attacks via Adversarially Adaptive Training. - Minh-Hao Van; Wei Du 009; Xintao Wu; Feng Chen 001; Aidong Lu (IEEE Big Data, 2022)

Poisoning Attacks on Fair Machine Learning. - Minh-Hao Van; Wei Du 009; Xintao Wu; Aidong Lu (DASFAA (1), 2022)

HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. - Minh-Hao Van; Alycia N. Carey; Xintao Wu (ICDM, 2023)

Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model. - Minh-Hao Van; Xintao Wu (CoRR, 2023)

Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis. - Prateek Verma; Minh-Hao Van; Xintao Wu (IEEE Big Data, 2024)

On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study. - Minh-Hao Van; Prateek Verma; Xintao Wu (CHASE, 2024)

Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions. - Alycia N. Carey; Minh-Hao Van; Xintao Wu (IJCNN, 2024)

Robust Influence-Based Training Methods for Noisy Brain MRI. - Minh-Hao Van; Alycia N. Carey; Xintao Wu (PKDD (4), 2024)

In-Context Learning Demonstration Selection via Influence Analysis. - Vinay M. S.; Minh-Hao Van; Xintao Wu (CoRR, 2024)

Fair In-Context Learning via Latent Concept Variables. - Karuna Bhaila; Minh-Hao Van; Kennedy Edemacu; Chen Zhao 010; Feng Chen 001; Xintao Wu (CoRR, 2024)

Soft Prompting for Unlearning in Large Language Models. - Karuna Bhaila; Minh-Hao Van; Xintao Wu (NAACL (Long Papers), 2025)

Detecting and Mitigating Hateful Content in Multimodal Memes with Vision-Language Models. - Minh-Hao Van; Xintao Wu (CoRR, 2025)

A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools. - Minh-Hao Van; Prateek Verma; Chen Zhao 010; Xintao Wu (CoRR, 2025)