activity
20242026
collaborators

11 papers

cs.AI2026

Mastermind: Strategy-grounded Learning for Repository-Scale Vulnerability Reproduction

Mingzhe Du, Luu Anh Tuan, Tianyi Wu +4

Repository-level vulnerability reproduction is a demanding software engineering (SE) task: an agent must inspect a codebase, infer the input grammar that reaches a vulnerable path,…

cs.CV2026

SafeRedir: Prompt Embedding Redirection for Robust Unlearning in Image Generation Models

Renyang Liu, Kangjie Chen, Han Qiu +4

Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from their training data, leading to…

cs.LG2026

Correct When Paired, Wrong When Split: Decoupling and Editing Modality-Specific Neurons in MLLMs

Tingchao Fu, Wenkai Wang, Fanxiao Li +6

Although Knowledge Editing provides an efficient mechanism for updating the knowledge of Multimodal Large Language Models (MLLMs), we find that current paradigms still suffer from…

cs.CV2026

CAAP: Capture-Aware Adversarial Patch Attacks on Palmprint Recognition Models

Renyang Liu, Jiale Li, Jie Zhang +6

Palmprint recognition is deployed in security-critical applications, including access control and palm-based payment, due to its contactless acquisition and highly discriminative r…

cs.CV2026

REFORGE: Multi-modal Attacks Reveal Vulnerable Concept Unlearning in Image Generation Models

Yong Zou, Haoran Li, Fanxiao Li +5

Recent progress in image generation models (IGMs) enables high-fidelity content creation but also amplifies risks, including the reproduction of copyrighted content and the generat…

cs.CV2026

Image Can Bring Your Memory Back: A Novel Multi-Modal Guided Attack against Image Generation Model Unlearning

Renyang Liu, Guanlin Li, Tianwei Zhang +1

Recent advances in image generation models (IGMs), particularly diffusion-based architectures such as Stable Diffusion (SD), have markedly enhanced the quality and diversity of AI-…