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Found 3 papers, 2 papers with code
ConStat: Performance-Based Contamination Detection in Large Language Models
To overcome these limitations, we propose a novel definition of contamination as artificially inflated and non-generalizing benchmark performance instead of the inclusion of benchmark samples in the training data.
Evading Data Contamination Detection for Language Models is (too) Easy
Large language models are widespread, with their performance on benchmarks frequently guiding user preferences for one model over another.
Controlled Text Generation via Language Model Arithmetic
In addition, the framework allows for more precise control of generated text than direct prompting and prior controlled text generation (CTG) techniques.
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