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EvalDetectBench: A Benchmark for Measuring Evaluation Awareness in Frontier Language Models
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evaluationbenchmarkingAI safetylanguage models
2609.01611
Builder Relevance
2h ago70%
Abstract
EvalDetectBench is a benchmark for measuring evaluation awareness in large language models, addressing the validity of evaluation results in AI safety frameworks.
Reality Card
Core Claim
EvalDetectBench introduces a new benchmark that allows practitioners to measure how reliably frontier LLMs recognize evaluations and assess the detectability of individual benchmarks.
Method / Result
The benchmark corrects for systematic bias, with the identity of the model accounting for 11.25% of measurement variance.
Limitations
The methodology may still be influenced by the specific models and prompts used, which could affect reproducibility.
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