4 papers
Semantics-Aware Bilevel Co-Evolution: Towards Automated Multicomponent Algorithm Design
Zhiyao Zhang, Shenghao Wu, Xingyu Wu +1
LLM-assisted evolutionary search (LES) has emerged as a promising paradigm for automated algorithm design. However, existing methods usually suffer from two inherent limitations wh…
Fine-Grained Model Merging via Modular Expert Recombination
Haiyun Qiu, Xingyu Wu, Liang Feng +1
Model merging constructs versatile models by integrating task-specific models without requiring labeled data or expensive joint retraining. Although recent methods improve adaptabi…
A Theoretical Analysis of Analogy-Based Evolutionary Transfer Optimization
Xiaoming Xue, Liang Feng, Yinglan Feng +3
Evolutionary transfer optimization (ETO) has been gaining popularity in research over the years due to its outstanding knowledge transfer ability to address various challenges in o…
Design Principle Transfer in Neural Architecture Search via Large Language Models
Xun Zhou, Xingyu Wu, Liang Feng +2
Transferable neural architecture search (TNAS) has been introduced to design efficient neural architectures for multiple tasks, to enhance the practical applicability of NAS in rea…