collaborators

11 papers

cs.CR2026

VirusCascade: Hijacking Collaborative Reflection in LLM-Powered Recommender Agents

Yurong Hao, Wen Zhou, Guowei Guan +3

Advancing beyond traditional static scoring models, LLM-powered agentic recommender systems (LLM-ARS) instantiate users and items as autonomous agents, whose semantic states are dy…

cs.CR2026

What Does It Mean to Forget a Person? Individual-Level Unlearning in Vision-Language Models

Xiongtao Sun, Hui Li, Tiantong Wu +3

Erasing individual identities from Vision-Language Models (VLMs) is uniquely challenging because personal data is entangled across modalities rather than stored as isolated attribu…

cs.CV2026

Relevance Does Not Imply Applicability: Experience Activation for Personal GUI Agents

Fuyao Zhang, Xuan Wang, Zherui Li +3

Personal Graphical User Interface (GUI) agents rely on interaction history to infer what a user wants from ambiguous instructions and to anticipate recurring routines. Existing app…

cs.CR2026

SynChain: Inducing Computer-Use Agent Systems to Construct Their Own Attack Chains

Fuyao Zhang, Jiaming Zhang, Che Wang +7

Computer-use agents~(CUAs) have transformed large language models into persistent execution systems capable of generating, storing, and reusing artifacts like skills and memory ent…

cs.CR2026

Adversarial Attacks for Good: A Survey of Proactive Protection across the Visual Content Lifecycle

Jiaming Zhang, Boyang Chen, Zherui Li +14

Once visual content enters an AI pipeline, its owner often retains little technical control over how it is used. Legal and regulatory remedies can address misuse, but many technica…

cs.AI2026

XDomainBench: Diagnosing Reasoning Collapse in High-Dimensional Scientific Knowledge Composition

Gong Zhiren, Tiantong Wu, Jiaming Zhang +9

Large Language Models (LLMs) are increasingly deployed for knowledge synthesis, yet their capacity for compositional generalization in scientific knowledge remains under-characteri…

cs.AI2026

ICON: Indirect Prompt Injection Defense for Agents based on Inference-Time Correction

Che Wang, Fuyao Zhang, Jiaming Zhang +6

Large Language Model (LLM) agents are susceptible to Indirect Prompt Injection (IPI) attacks, where malicious instructions in retrieved content hijack the agent's execution. Existi…

cs.CR2026

VENOMREC: Cross-Modal Interactive Poisoning for Targeted Promotion in Multimodal LLM Recommender Systems

Guowei Guan, Yurong Hao, Jiaming Zhang +6

Multimodal large language models (MLLMs) are pushing recommender systems (RecSys) toward content-grounded retrieval and ranking via cross-modal fusion. We find that while cross-mod…

cs.CR2025

DualTAP: A Dual-Task Adversarial Protector for Mobile MLLM Agents

Fuyao Zhang, Jiaming Zhang, Che Wang +6

The reliance of mobile GUI agents on Multimodal Large Language Models (MLLMs) introduces a severe privacy vulnerability: screenshots containing Personally Identifiable Information…

cs.LG2025

Oblivionis: A Lightweight Learning and Unlearning Framework for Federated Large Language Models

Fuyao Zhang, Xinyu Yan, Tiantong Wu +7

Large Language Models (LLMs) increasingly leverage Federated Learning (FL) to utilize private, task-specific datasets for fine-tuning while preserving data privacy. However, while…

cs.CR2025

Verifiably Forgotten? Gradient Differences Still Enable Data Reconstruction in Federated Unlearning

Fuyao Zhang, Wenjie Li, Yurong Hao +3

Federated Unlearning (FU) has emerged as a critical compliance mechanism for data privacy regulations, requiring unlearned clients to provide verifiable Proof of Federated Unlearni…