Datasets:
| cff-version: 1.2.0 | |
| title: 'CropMath: An Objective Benchmark for Mechanistic Formula Reasoning in Agricultural | |
| Large Language Models' | |
| message: If you use this dataset, please cite it using the metadata below. | |
| type: dataset | |
| authors: | |
| - family-names: Ma | |
| given-names: Yuanyuan | |
| affiliation: Nanjing Agricultural University | |
| year: 2026 | |
| license: CC-BY-4.0 | |
| repository-code: https://github.com/YuanyuanMa03/CropMath | |
| abstract: CropMath is an objective benchmark for evaluating mechanistic formula reasoning | |
| in agricultural large language models. It contains 62 formulas from 4 public family | |
| categories (growth_yield, carbon_nitrogen_cycle, methane_emission, environmental_response), | |
| 6 knowledge-ablation conditions, and 4 reasoning modes. Ground-truth answers are | |
| derived deterministically from the documented mathematical expressions. | |
| keywords: | |
| - agricultural science | |
| - mechanistic formula reasoning | |
| - formula reasoning | |
| - numerical reasoning | |
| - benchmark | |
| - knowledge ablation | |
| - LLM evaluation | |