LLM-SR — security grade SAFE, quality 74/100

Security audit verdict: SAFE · quality 74/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by deep-symbolic-mathematics · Agent Tool · ★ 267

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

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About LLM-SR

: Scientific Equation Discovery and Symbolic Regression via Programming with LLMs Official Implementation of paper LLM-SR: Scientific Equation Discovery via Programming with Large Language Models (ICLR 2025 Oral). Updates Our recent more comprehensive benchmark LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models (to appear at ICML 2025 as Oral) is released following this work to effectively test LLM-based scientific equation discovery methods beyond memorization. Check out the benchmark data on huggingface and evaluation codes here. Overview In this paper, we introduce LLM-SR, a novel approach for scientific equation discovery and symbolic regression that leverages strengths of Large Language Models (LLMs). LLM-SR combines LLMs' scientific knowledge and code generation capabilities with evolutionary search to discover accurate and interpretable equations from d

ai4codeai4mathai4scienceequation-discoverylarge-language-modelsllm-agentprogram-synthesisscientific-discoverysymbolic-regression

Quick Facts

Stars267
Forks51
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score73.9784056248711/100
Open Issues8
Last Updated2025-07-31
Created2024-04-19
Platformspython
Est. Tokens~598k

Compatible Skills

These tools work well together with LLM-SR for enhanced workflows:

  • synalinks-skills — semantic(0.36)+complementary+same_lang+similar_pop+shared_platform (58%)
  • SimplerLLM — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (54%)
  • code-index-mcp — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (52%)
  • mxcp — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (52%)
  • app-controller — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (52%)

LLM-SR alternative? Top 6 similar tools

Looking for a LLM-SR alternative? If you're comparing LLM-SR with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • PairCoder by nju-websoft · ⭐ 113

    A Pair Programming Framework for Code Generation via Multi-Plan Exploration and Feedback-Driven Refinement, AS

  • CORAL by Human-Agent-Society · ⭐ 961

    Open-source autoresearch powered by autonomous coding agents. Run Claude Code, OpenCode, and Codex with gradin

  • bigcodebench by bigcode-project · ⭐ 519

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  • promptdesk by promptdesk · ⭐ 100

    Promptdesk is a tool designed for effectively creating, organizing, and evaluating prompts and large language

  • wisp-science by xuzhougeng · ⭐ 1.2k

    Open-source, local-first desktop AI research workbench for scientific computing with Python/R, MCP bioinformat

  • tribe by StreetLamb · ⭐ 1.1k

    Low code tool to rapidly build and coordinate multi-agent teams

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Frequently Asked Questions

What is LLM-SR?

LLM-SR is [ICLR 2025 Oral] This is the official repo for the paper "LLM-SR" on Scientific Equation Discovery and Symbolic Regression with Large Language Models. It is categorized as a Agent Tool with 267 GitHub stars.

What programming language is LLM-SR written in?

LLM-SR is primarily written in Python. It covers topics such as ai4code, ai4math, ai4science.

How do I install or use LLM-SR?

You can find installation instructions and usage details in the LLM-SR GitHub repository at github.com/deep-symbolic-mathematics/LLM-SR. The project has 267 stars and 51 forks, indicating an active community.

What license does LLM-SR use?

LLM-SR is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to LLM-SR?

The top alternatives to LLM-SR on Agent Skills Hub include PairCoder, CORAL, bigcodebench. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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