5 papers
FuzzingBrain V2: A Multi-Agent LLM System for Automated Vulnerability Discovery and Reproduction
Ze Sheng, Zhicheng Chen, Qingxiao Xu +2
Software vulnerabilities pose critical security threats, with nearly 50,000 CVEs reported in 2025. While Large Language Models (LLMs) show promise for automated vulnerability detec…
Helix: A Dual-Helix Co-Evolutionary Multi-Agent System for Prompt Optimization and Question Reformulation
Kewen Zhu, Liping Yi, Zhiming Zhao +2
Automated prompt optimization (APO) aims to improve large language model performance by refining prompt instructions. However, existing methods are largely constrained by fixed pro…
FedPDPO: Federated Personalized Direct Preference Optimization for Large Language Model Alignment
Kewen Zhu, Liping Yi, Zhiming Zhao +3
Aligning large language models (LLMs) with human preferences in federated learning (FL) is challenging due to decentralized, privacy-sensitive, and highly non-IID preference data.…
FedAdamW: A Communication-Efficient Optimizer with Convergence and Generalization Guarantees for Federated Large Models
Junkang Liu, Fanhua Shang, Hongying Liu +5
AdamW has become one of the most effective optimizers for training large-scale models. We have also observed its effectiveness in the context of federated learning (FL). However, d…
Knowledge Graph for Intelligent Generation of Artistic Image Creation: Constructing a New Annotation Hierarchy
Jia Kaixin, Zhu Kewen, Deng Huanghuang +5
Our study aims to establish a unified, systematic, and referable knowledge framework for the annotation of art image datasets, addressing issues of ambiguous definitions and incons…