Equation 9 · The Hardest Unsolved Problems in Open-Weight AI
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A simple decomposition makes clear why this is a measurement problem and not merely an inconvenience. Let be an observed benchmark score, the underlying capability the benchmark intends to measure, and c the fraction of test instances the model has effectively memorized, whether verbatim or through a rephrased variant. If a memorized instance is answered correctly with certainty, then approximately
Sources cited in the article section
- [13] Hugging Face Releases Open LLM Leaderboard 2: A Major Upgrade Featuring Tougher Benchmarks, Fairer Scoring, and Enhanced Community Collaboration ↗
- [12] It's Been a Wild Ride, Folks (End of the Open LLM Leaderboard) ↗
- [9] Detecting Pretraining Data from Large Language Models ↗
- [10] Rethinking Benchmark and Contamination for Language Models with Rephrased Samples ↗
- [11] On the Fragility of Benchmark Contamination Detection in Reasoning Models ↗
These citations give research context. Read each source to check which claims it supports.