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Qinglong Hu

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Preprint Aug 2026

Beyond Average Performance: Dynamic Instance Clustering and Specialized Algorithm Design in LLM-Assisted Evolutionary Search

DyCA treats instance clustering as a co-evolving component within the search process, reusing accumulated evaluation data as feature-free signals to progressively partition instances with similar algorithmic response patterns, thereby enabling finer-grained and more adaptive guidance for specialized algorithm design.

Qinglong Hu, Qingfu Zhang, Fei Liu et al. · 0 citations
2025

Partition to Evolve: Niching-enhanced Evolution with LLMs for Automated Algorithm Discovery

This work proposes a general LES framework that incorporates feature-assisted niche construction within abstract search spaces, enabling the seamless integration of niche-based search strategies from evolutionary computation and introduces PartEvo (Partition to Evolve), an LES method that combines niche collaborative search and advanced prompting strategies to improve algorithm discovery efficiency.

Qinglong Hu, Qingfu Zhang · 10 citations · ⚡3