ChemCoTBench-V2 is a new rule-verifiable benchmark with 5,620 samples across 18 tasks that evaluates LLM chemical reasoning traces using deterministic chemistry rules and reference traces rather than final answers alone.
Chemeval: a comprehensive multi-level chemical evaluation for large language models
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MLLMs exhibit a consistent recognition-reasoning inversion on discrete visual symbols across domains, underperforming on elementary perception while appearing competent on higher-level reasoning via linguistic compensation.
ChemDFM-R is a chemical reasoning LLM trained via a four-stage pipeline on the ChemFG dataset of functional-group annotations for molecules and reactions, reaching performance comparable to or better than commercial models on chemical benchmarks.
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ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge
ChemDFM-R is a chemical reasoning LLM trained via a four-stage pipeline on the ChemFG dataset of functional-group annotations for molecules and reactions, reaching performance comparable to or better than commercial models on chemical benchmarks.