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MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- MOT-SR combines large language models with external analytical tools to discover scientific equations from data, optimizing simultaneously for accuracy, complexity, and generalization.
- 为何重要
- Relevant for engineers building scientific modeling systems, symbolic regression tools, or physics-informed machine learning pipelines that need interpretable equations.
- 注意
- Paper is recent and from arXiv; real-world applicability beyond the tested 40 tasks and gravitational-wave modeling domain remains unvalidated in production systems.
收听本摘要
- llm
- language model
- eval
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