---
title: "Evaluating SageMath-Augmented LLM Agents for Computational and Experimental Mathematics — Stuff That Spins"
description: "arXiv:2607.06820v1 Announce Type: new Abstract: Recent advances in AI for Mathematics have focused largely on autoformalization and theorem proving, leaving th…"
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date: "2026-07-09T04:00:00+00:00"
modified: "2026-07-09T06:02:21.592423+00:00"
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# Evaluating SageMath-Augmented LLM Agents for Computational and Experimental Mathematics

**Source:** Unknown  
**Published:** July 9, 2026  
**Original:** https://arxiv.org/abs/2607.06820  

## On this page

- [Overview](#overview)

<a id="overview"></a>

## Overview

arXiv:2607.06820v1 Announce Type: new Abstract: Recent advances in AI for Mathematics have focused largely on autoformalization and theorem proving, leaving the role of Computer Algebra Systems (CAS) in agentic LLM workflows underexplored. We propose a ReAct-style agentic setup that combines LLM reasoning with verifiable feedback from SageMath, together with Context7 for the up-to-date documentation. We evaluate this agentic setup across frontier models for solving research-level mathematical pr

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