Multi-Modal Learning meets Genetic Programming: Analyzing Alignment in Latent Space Optimization 事件

Multi-Modal Learning meets Genetic Programming: Analyzing Alignment in Latent Space Optimization arXiv:2604.08324v3 Announce Type: replace-cross Abstract: Symbolic regression (SR) aims to discover mathematical expressions from data, a task traditionally tackled using Genetic Programming (GP) through combinatorial search over symbolic structures. Latent Space Optimization (LSO) methods use neural encoders to map symbolic expressions into continuous spaces, transforming the combinatorial search i