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@@ -8,10 +8,11 @@ tags:
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  pretty_name: CoCoNUT
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  size_categories:
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  - 1K<n<10K
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- dataset_info:
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- description: >
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- CoCoNUT investigates the capabilities of selected Large Language Models on understanding structural code execution. The dataset includes tasks where models reproduce the code lines executed for specific input arguments, testing advanced code concepts such as Object-Oriented Programming (OOP), Concurrency, and Recursion. The dataset contains short programs, their traces, and evaluation metrics from HumanEval and complex scenarios.
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- visualizations:
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- - url: https://raw.githubusercontent.com/ClaasBeger/StructuralCodeUnderstanding/Visualizations/Bucket_linePlot_direct_overlap.png
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- description: Task Performance given Trace Length Buckets.
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  ---
 
 
 
 
 
 
 
 
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  pretty_name: CoCoNUT
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  size_categories:
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  - 1K<n<10K
 
 
 
 
 
 
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  ---
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+
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+ ## dataset_info:
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+ CoCoNUT investigates the capabilities of selected Large Language Models on understanding structural code execution. The dataset includes tasks where models reproduce the code lines executed for specific input arguments, testing advanced code concepts such as Object-Oriented Programming (OOP), Concurrency, and Recursion. The dataset contains short programs, their traces, and evaluation metrics from HumanEval and complex scenarios.
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+ The Code can be found at the github repository: https://github.com/ClaasBeger/StructuralCodeUnderstanding
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+
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+ Model Performance:
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+ ![Model Performance](Bucket_linePlot_direct_overlap.png "Model Performance on CoCoNUT")