Showing cs.NEShow all
3 papers · 1 filter
cs.NE2026
Benchmarking Zero-Shot LLM-Generated Parent Selection in Genetic Programming for Symbolic Regression
Hengzhe Zhang, Qi Chen, Bing Xue +2
Parent selection significantly affects exploration, exploitation, and complexity control in genetic programming (GP) for symbolic regression. It is unclear whether large language m…
cs.NE2025
Symbolically Regressing Fish Biomass Spectral Data: A Linear Genetic Programming Method with Tunable Primitives
Zhixing Huang, Bing Xue, Mengjie Zhang +3
Machine learning techniques play an important role in analyzing spectral data. The spectral data of fish biomass is useful in fish production, as it carries many important chemistr…
cs.NE2025
LLM-Meta-SR: In-Context Learning for Evolving Selection Operators in Symbolic Regression
Hengzhe Zhang, Qi Chen, Bing Xue +2
Large language models (LLMs) have revolutionized algorithm development, yet their application in symbolic regression, where algorithms automatically discover symbolic expressions f…