CME-SpectrumBench: Can LLMs Analyze Condensed Matter Spectral Data?

arXiv cs.AIOctober 20, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2610.24304v1 Announce Type: new Abstract: Large Language Models (LLMs) are presently well assessed by expert-level mathematics and physics benchmarks which focus on theoretical, symbolic reasoning. However, we lack experimental benchmarks that evaluate data analysis in frontier research problems, a capability that future domain-specific foundation models must have. To this end, we present CME-SpectrumBench, an expert-designed benchmark consisting of 190 questions that measures how reliably frontier LLMs analyze research-level spectral scientific data in condensed matter experiments (CME). Using simulated CME spectral data, we prompt models to identify structures from 2D intensity array

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