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  path: data/test-*
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  # Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
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- CanItEdit is a benchmark for evaluating LLMs on instructional code editing, the task of updating a program given a natural language instruction. The benchmark contains 54 hand-crafted Python programs with before and after code blocks, two types of natural language instructions (descriptive and lazy), and a hidden test suite.
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  The dataset’s dual natural language instructions test model efficiency in two scenarios:
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  1) Descriptive: Detailed instructions replicate situations where users provide specific specifications or
 
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  path: data/test-*
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  # Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
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+ CanItEdit is a benchmark for evaluating LLMs on instructional code editing, the task of updating a program given a natural language instruction. The benchmark contains 105 hand-crafted Python programs with before and after code blocks, two types of natural language instructions (descriptive and lazy), and a hidden test suite.
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  The dataset’s dual natural language instructions test model efficiency in two scenarios:
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  1) Descriptive: Detailed instructions replicate situations where users provide specific specifications or