AgenticMathQA¶
Product or Programme · All products and programmes
Evidence · 3 claims (3 for) · 1 study (1 design),q2· 0 of 1 report an effect size · 3 claims rest on one study
Description¶
AgenticMathQA is a curated 30K, 60K, or 90K mathematical problem-solution dataset released by Liu et al. for training large language models on mathematical reasoning.
Components¶
Claims¶
- Fine-tuning LLMs on 30K-90K AgenticMath samples matches or surpasses baselines trained on 400K-2.3M samples on math reasoning benchmarks [+M]
- At 30K and 60K data scales, AgenticMath outperforms all compared baselines across four base models on six math benchmarks [+W]
- Increasing AgenticMath-generated training data from 7.5K to 22.5K samples yields consistent accuracy gains for Llama3-8B across benchmarks [+W]
Related Products and Programmes¶
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Key Sources¶
- Xianyang Liu, Yilin Liu, Shuai Wang, Hao Cheng, Andrew Estornell, Yuzhi Zhao, Jun Shu, Jiaheng Wei. (2025). AgenticMath: Enhancing LLM Reasoning via Agentic-based Math Data Generation. arXiv preprint. https://arxiv.org/abs/2510.19361
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
agenticmathqa |
title |
AgenticMathQA |
description |
AgenticMathQA is a curated 30K, 60K, or 90K mathematical problem-solution dataset released by Liu et al. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
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