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@@ -6,6 +6,8 @@ language:
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  - en
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  size_categories:
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  - n<1K
 
 
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  ---
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@@ -32,6 +34,7 @@ HumanEvalComm is a benchmark dataset for evaluating the communication skills of
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  | 2cp | | ✔️ | ✔️ | 34 |
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  | 2ap | ✔️ | | ✔️ | 74 |
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  | **Total** | -- | -- | -- | 762 |
 
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  <sub>
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  *Note*: The smaller size for 2ac (same applies for 2cp and 2ap) is because we directly applied a combination of two clarification types from 1a, 1c strictly, and we create a new modified problem as 2ac only if applying a combination of 1a and 1c leads to a new problem description that is different from either 1a or 1c. 2cp and 2ap have smaller counts because the ambiguous (a) or inconsistent (c) parts are removed in (p) for a large number of problems.
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  </sub>
@@ -75,4 +78,4 @@ humanevalcomm = load_dataset("jie-jw-wu/HumanEvalComm", split="test")
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  journal={arXiv preprint arXiv:2406.00215},
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  year={2024}
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  }
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- ```
 
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  - en
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  size_categories:
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  - n<1K
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+ tags:
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+ - code generation
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  ---
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  | 2cp | | ✔️ | ✔️ | 34 |
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  | 2ap | ✔️ | | ✔️ | 74 |
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  | **Total** | -- | -- | -- | 762 |
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+
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  <sub>
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  *Note*: The smaller size for 2ac (same applies for 2cp and 2ap) is because we directly applied a combination of two clarification types from 1a, 1c strictly, and we create a new modified problem as 2ac only if applying a combination of 1a and 1c leads to a new problem description that is different from either 1a or 1c. 2cp and 2ap have smaller counts because the ambiguous (a) or inconsistent (c) parts are removed in (p) for a large number of problems.
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  </sub>
 
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  journal={arXiv preprint arXiv:2406.00215},
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  year={2024}
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  }
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+ ```