3 papers
cs.NE2026
Evolving Interdependent Operators with Large Language Models for Multi-Objective Combinatorial Optimization
Junhao Qiu, Xin Chen, Liang Ge +3
Neighborhood search operators are critical to the performance of Multi-Objective Evolutionary Algorithms (MOEAs) and rely heavily on expert design. Although recent LLM-based Automa…
cs.LG2025
EvoEngineer: Mastering Automated CUDA Kernel Code Evolution with Large Language Models
Ping Guo, Chenyu Zhu, Siyuan Chen +4
CUDA kernel optimization has become a critical bottleneck for AI performance, as deep learning training and inference efficiency directly depends on highly optimized GPU kernels. D…
cs.SE2025
Evolution of Kernels: Automated RISC-V Kernel Optimization with Large Language Models
Siyuan Chen, Zhichao Lu, Qingfu Zhang
Automated kernel design is critical for overcoming software ecosystem barriers in emerging hardware platforms like RISC-V. While large language models (LLMs) have shown promise for…