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When Better Means Less: Quantifying What Benchmarks Miss Between Model Generations. 2,310 controlled comparisons show GPT-5 series lost 6.7x creativity and gained 4.4x false refusals vs chatgpt-4o-latest — invisible to standard benchmarks.
Code, data, and results for "The Correlation Mirage: Benchmark Dependence Collapses for Top-Performing LLMs" (EMNLP 2026). Copula-based tail dependence analysis of LLM benchmark suites.
llmverify is a lightweight Python tool for externally auditing LLM APIs and verifying whether custom providers and resellers truly serve the frontier models they claim to run, using layered probes and benchmark-based statistics.
Does a benchmark overstate operational skill when the distribution shift is ordinary and physical? Houston ground-level ozone exceedance forecasting — the control domain in a multi-domain study of benchmark-vs-operational ML performance.
How much of a phishing benchmark's score is detection skill, and how much is an artifact of how the dataset was built? A zero-parameter regex scores TSS 0.99 on PhiUSIIL; the trained model scores 0.000 on live data.
Audit of BixBench, FutureHouse's bioinformatics-agent benchmark: replicated runs, replicated grading, re-derived answer keys — and what a single pooled score hides.