7 papers
UniErase: Towards Balanced and Precise Unlearning in Language Models
Miao Yu, Liang Lin, Guibin Zhang +7
Large language models (LLMs) require iterative updates to address the outdated information problem, where LLM unlearning offers an approach for selective removal. However, mainstre…
G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks
Guibin Zhang, Yanwei Yue, Xiangguo Sun +6
Recent advancements in large language model (LLM)-based agents have demonstrated that collective intelligence can significantly surpass the capabilities of individual agents, prima…
DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting
Hao Wu, Haomin Wen, Guibin Zhang +5
The ever-increasing sensor service, though opening a precious path and providing a deluge of earth system data for deep-learning-oriented earth science, sadly introduce a daunting…
CaT-GNN: Enhancing Credit Card Fraud Detection via Causal Temporal Graph Neural Networks
Yifan Duan, Guibin Zhang, Shilong Wang +6
Credit card fraud poses a significant threat to the economy. While Graph Neural Network (GNN)-based fraud detection methods perform well, they often overlook the causal effect of a…
Mind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia
Miao Yu, Junyuan Mao, Guibin Zhang +7
Research into the external behaviors and internal mechanisms of large language models (LLMs) has shown promise in addressing complex tasks in the physical world. Studies suggest th…
NetSafe: Exploring the Topological Safety of Multi-agent Networks
Miao Yu, Shilong Wang, Guibin Zhang +6
Large language models (LLMs) have empowered nodes within multi-agent networks with intelligence, showing growing applications in both academia and industry. However, how to prevent…