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LLMs evolve tools and policies for scientific equation discovery

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework for scientific equation discovery using large language models (LLMs). This system couples the evolution of computational tools with the LLM's tool-use policy, allowing both to improve from the same error signal. The tool-evolution phase enables the agent to grow its library of executable tools by diagnosing and correcting its own failures, while the policy-evolution phase fine-tunes the LLM on successful tool-use trajectories. This integrated approach significantly enhances the model's ability to solve complex scientific problems, achieving high accuracy on various benchmarks. AI

IMPACT This framework could accelerate scientific discovery by enabling LLMs to more effectively discover and utilize computational tools.

RANK_REASON The item is an academic paper detailing a new framework for scientific discovery using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLMs evolve tools and policies for scientific equation discovery

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14 / 100
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The item is an academic paper detailing a new framework for scientific discovery using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Pengze Li, Jiaquan Zhang, Encheng Su, Yunbo Long, Zihang Zeng, Xinping Liu, Han Zhang, Junchi Yu, Shixiang Tang, Aoran Wang, Xi Chen ·

    Coupled Harness--Model Evolution for Scientific Equation Discovery

    arXiv:2610.17740v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to discover scientific equations from experimental data. Such a discovery system has two parts that must work together: a library of executable computational tools and the model's t…

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