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The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language Models
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The recent rise in the popularity of large language models has spurred the development of extensive code datasets needed to train them. This has left limited code available for collection and use in the downstream investigation of specific behaviors, or evaluation of large language models without suffering from data contamination. To address this problem, we release The Heap, a large multilingual dataset covering 57 programming languages that has been deduplicated with respect to other open datasets of code, enabling researchers to conduct fair evaluations of large language models without significant data cleaning overhead.
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$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection
DroidCollection and DroidDetect provide the largest open resource for detecting AI-generated code, including adversarial 'humanized' samples, and show that training on a small amount of such data restores detector robustness.
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