7 citations · 7 across the 5 of their papers we have counts for
7 papers
Evolutionary Intelligence for Scientific Discovery: From Evolutionary Computation to Cumulative Discovery Systems
Chao Wang, Lingling Li, Fang Liu +1
Artificial intelligence (AI) is shifting scientific discovery from task-specific workflows towards autonomous systems that organize exploration with experimental and human feedback…
Model Merging to Evolution: Parameter Space Exploration for Expert Models
Chao Wang, Yuchen Guo, Zheng Tan +4
Model merging integrates the capabilities of multiple expert models to create strong models for multiple tasks without additional training, thereby reducing computational resource…
Task-free Adaptive Meta Black-box Optimization
Chao Wang, Licheng Jiao, Lingling Li +4
Handcrafted optimizers become prohibitively inefficient for complex black-box optimization (BBO) tasks. MetaBBO addresses this challenge by meta-learning to automatically configure…
Learning Evolution via Optimization Knowledge Adaptation
Chao Wang, Lingling Li, Licheng Jiao +3
The iterative search process of evolutionary algorithms (EAs) encapsulates optimization knowledge within historical populations and fitness evaluations. Effective utilization of th…
Knowledge-aware Evolutionary Graph Neural Architecture Search
Chao Wang, Jiaxuan Zhao, Lingling Li +4
Graph neural architecture search (GNAS) can customize high-performance graph neural network architectures for specific graph tasks or datasets. However, existing GNAS methods begin…
Automatic Graph Topology-Aware Transformer
Chao Wang, Jiaxuan Zhao, Lingling Li +3
Existing efforts are dedicated to designing many topologies and graph-aware strategies for the graph Transformer, which greatly improve the model's representation capabilities. How…
When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges
Chao Wang, Jiaxuan Zhao, Licheng Jiao +3
Pre-trained large language models (LLMs) exhibit powerful capabilities for generating natural text. Evolutionary algorithms (EAs) can discover diverse solutions to complex real-wor…