mention paper in readme
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# 🌱⚙️
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This repository contains data associated with
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* statistics about repositories from GitHub Search under `ghs/data` folder;
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* several data splits under `splits` folder;
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4. We filter the repositories from previous step to keep only those without Docker-related configuration files: `splits/python_single_dm_in_root_folder_no_docker.jsonl`
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5. We filter the repositories from previous step to keep only those that our deterministic script couldn't configure correctly: `splits/python_baseline_failure.jsonl`
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The list of 329 repositories from our benchmark is available in `splits/python_baseline_failure.jsonl`. For convenience, the final set of Git repositories is also stored separately under `repos/final/python`.
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# 🌱⚙️ EnvBench
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This repository contains data associated with EnvBench benchmark from [**EnvBench: A Benchmark for Automated Environment Setup**](https://arxiv.org/abs/2503.14443).
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It contains:
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* statistics about repositories from GitHub Search under `ghs/data` folder;
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* several data splits under `splits` folder;
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4. We filter the repositories from previous step to keep only those without Docker-related configuration files: `splits/python_single_dm_in_root_folder_no_docker.jsonl`
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5. We filter the repositories from previous step to keep only those that our deterministic script couldn't configure correctly: `splits/python_baseline_failure.jsonl`
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The list of 329 repositories from our benchmark is available in `splits/python_baseline_failure.jsonl`. For convenience, the final set of Git repositories is also stored separately under `repos/final/python`.
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## 📚 Citation
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If you find this work useful for your research, please consider the following citation:
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```
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@inproceedings{eliseeva2025envbench,
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title={EnvBench: A Benchmark for Automated Environment Setup},
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author={Aleksandra Eliseeva and Alexander Kovrigin and Ilia Kholkin and Egor Bogomolov and Yaroslav Zharov},
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booktitle={ICLR 2025 Third Workshop on Deep Learning for Code},
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year={2025},
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url={https://openreview.net/forum?id=izy1oaAOeX}
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}
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```
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