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cs.AI2026
EvoPINN: Agentic Discovery of Executable Algorithms for Physics-Informed Neural Networks
Peng Yin, Kai Li, Yifan Zhang +1
Physics-informed neural networks (PINNs) have emerged as a powerful paradigm for solving partial differential equations (PDEs), yet their performance heavily relies on the manual,…
cs.AI2026
Game-Theoretic Co-Evolution for LLM-Based Heuristic Discovery
Xinyi Ke, Kai Li, Junliang Xing +2
Large language models (LLMs) have enabled rapid progress in automatic heuristic discovery (AHD), yet most existing methods are predominantly limited by static evaluation against fi…