Execution-grounded evaluation reveals hidden failures in language-model calculations for environmental science
Large language models are increasingly used for quantitative work in the environmental sciences, yet existing evaluations score only final answers, leaving calculation process unobserved. Here we introduce AtmosCoder-Bench, an execution-grounded benchmark that makes the calculation process visible. Built through a transferable semi-automated pipeline (436 problems, 3,910 variants, 7,029 graded quantities), every problem is validated to be unambiguous and human-solvable, with uniquely verifiable answers. We find that (i) multiple-choice formats inflate measured accuracy by at least 12 percentage points; (ii) many failures arise not from missing knowledge but from models failing to apply kn...
| Authors | Maohao Ran, Chendong Ma, Yanting Zhang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 19 August 2026 |
| Last updated at source | 19 August 2026 |
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