Author

Boxiao Wang

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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