108 citations · 252 across the 22 of their papers we have counts for
6 papers · 1 filter
Structure-Aware Cooperative Ensemble Evolutionary Optimization on Combinatorial Problems with Multimodal Large Language Models
Jie Zhao, Kang Hao Cheong
Evolutionary algorithms (EAs) have proven effective in exploring the vast solution spaces typical of graph-structured combinatorial problems. However, traditional encoding schemes,…
EduVerse: A User-Defined Multi-Agent Simulation Space for Education Scenario
Yiping Ma, Shiyu Hu, Buyuan Zhu +4
Reproducing cognitive development, group interaction, and long-term evolution in virtual classrooms remains a core challenge for educational AI, as real classrooms integrate open-e…
EduPersona: Benchmarking Subjective Ability Boundaries of Virtual Student Agents
Buyuan Zhu, Shiyu Hu, Yiping Ma +2
As large language models are increasingly integrated into education, virtual student agents are becoming vital for classroom simulation and teacher training. Yet their classroom-or…
Visual Evolutionary Optimization on Graph-Structured Combinatorial Problems with MLLMs: A Case Study of Influence Maximization
Jie Zhao, Kang Hao Cheong
Graph-structured combinatorial problems in complex networks are prevalent in many domains, and are computationally demanding due to their complexity and non-linear nature. Traditio…
Bridging Visualization and Optimization: Multimodal Large Language Models on Graph-Structured Combinatorial Optimization
Jie Zhao, Kang Hao Cheong, Witold Pedrycz
Graph-structured combinatorial challenges are inherently difficult due to their nonlinear and intricate nature, often rendering traditional computational methods ineffective or exp…
Can Large Language Models Be Trusted as Evolutionary Optimizers for Network-Structured Combinatorial Problems?
Jie Zhao, Tao Wen, Kang Hao Cheong
Large Language Models (LLMs) have shown strong capabilities in language understanding and reasoning across diverse domains. Recently, there has been increasing interest in utilizin…