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Add task category and library name to dataset card

#3
by nielsr HF Staff - opened
Files changed (1) hide show
  1. README.md +5 -4
README.md CHANGED
@@ -1,4 +1,8 @@
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  ---
 
 
 
 
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  dataset_info:
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  features:
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  - name: instance_id
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  data_files:
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  - split: test
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  path: data/test-*
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- license: cc-by-4.0
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  ---
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  # Dataset Summary
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  SWE-rebench is a large-scale dataset designed to support training and evaluation of LLM-based software engineering (SWE) agents, building upon and expanding our earlier release, [SWE-bench-extra](https://huggingface.co/datasets/nebius/SWE-bench-extra). It is constructed using a fully automated pipeline that continuously extracts real-world interactive SWE tasks from GitHub repositories at scale, as detailed in our paper [SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents](https://arxiv.org/abs/2505.20411). The dataset currently comprises over 21,000 issue–pull request pairs from 3,400+ Python repositories, each validated for correctness through automated environment setup and test execution. A curated subset of these tasks also forms the basis of our continuously updated [SWE-rebench leaderboard](https://swe-rebench.com/leaderboard).
@@ -162,5 +164,4 @@ The dataset is licensed under the Creative Commons Attribution 4.0 license. Howe
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  archivePrefix={arXiv},
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  primaryClass={cs.SE},
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  url={https://arxiv.org/abs/2505.20411}
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- }
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- ```
 
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  ---
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+ license: cc-by-4.0
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+ task_categories:
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+ - other
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+ library_name: datasets
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  dataset_info:
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  features:
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  - name: instance_id
 
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  data_files:
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  - split: test
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  path: data/test-*
 
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  ---
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  # Dataset Summary
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  SWE-rebench is a large-scale dataset designed to support training and evaluation of LLM-based software engineering (SWE) agents, building upon and expanding our earlier release, [SWE-bench-extra](https://huggingface.co/datasets/nebius/SWE-bench-extra). It is constructed using a fully automated pipeline that continuously extracts real-world interactive SWE tasks from GitHub repositories at scale, as detailed in our paper [SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents](https://arxiv.org/abs/2505.20411). The dataset currently comprises over 21,000 issue–pull request pairs from 3,400+ Python repositories, each validated for correctness through automated environment setup and test execution. A curated subset of these tasks also forms the basis of our continuously updated [SWE-rebench leaderboard](https://swe-rebench.com/leaderboard).
 
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  archivePrefix={arXiv},
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  primaryClass={cs.SE},
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  url={https://arxiv.org/abs/2505.20411}
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+ }