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mention paper in readme

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@@ -55,9 +55,11 @@ configs:
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- # 🌱⚙️ Environment Setup
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- This repository contains data associated with Environment Setup benchmark. 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;
@@ -88,4 +90,18 @@ The list of 665 repositories from our benchmark is available in `splits/jvm_base
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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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+
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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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+ ```