Author

Kai Li

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Jul 2026

MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models

Multi-Objective Tool-augmented Symbolic Regression (MOT-SR), a unified framework that integrates external analytical tools to extract structural priors and guide equation generation, while jointly optimizing for accuracy, complexity, and generalization via a multi-objective evaluation module that maintains a dynamic Pareto front is proposed.

Boxiao Wang, Runxian Wang, Kai Li et al. · arXiv.org · 0 citations

Jul 2026

EvoPINN: Agentic Discovery of Executable Algorithms for Physics-Informed Neural Networks

EvoPINN is proposed, an agentic framework that reformulates PINN development from labor-intensive manual design into a rigorous, execution-grounded algorithm discovery problem, and autonomously invented SLRC-PINN, a novel architecture whose performance gains persist under rigorous parameter-matched comparisons.

Peng Yin, Kai Li, Yifan Zhang et al. · arXiv.org · 0 citations