Datasets:
Tasks:
Question Answering
Modalities:
Text
Sub-tasks:
extractive-qa
Languages:
code
Size:
100K - 1M
License:
thepurpleowl
commited on
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Parent(s):
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README.md
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- **Homepage:** [Data](https://huggingface.co/datasets/thepurpleowl/codequeries)
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- **Repository:** [Code](https://github.com/thepurpleowl/codequeries-benchmark)
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- **Paper:** [
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### Dataset Summary
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@@ -119,4 +119,16 @@ The CodeQueries dataset is licensed under the [Apache-2.0](https://opensource.or
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### Citation Information
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-
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- **Homepage:** [Data](https://huggingface.co/datasets/thepurpleowl/codequeries)
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- **Repository:** [Code](https://github.com/thepurpleowl/codequeries-benchmark)
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- **Paper:** [Learning to Answer Semantic Queries over Code](https://arxiv.org/abs/2209.08372)
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### Dataset Summary
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### Citation Information
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```
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@misc{https://doi.org/10.48550/arxiv.2209.08372,
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doi = {10.48550/ARXIV.2209.08372},
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url = {https://arxiv.org/abs/2209.08372},
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author = {Sahu, Surya Prakash and Mandal, Madhurima and Bharadwaj, Shikhar and Kanade, Aditya and Maniatis, Petros and Shevade, Shirish},
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keywords = {Software Engineering (cs.SE), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
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title = {Learning to Answer Semantic Queries over Code},
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publisher = {arXiv},
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year = {2022},
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copyright = {Creative Commons Attribution 4.0 International}
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}
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```
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