Improve dataset card with task category, tags, and improved formatting
Browse filesThis PR improves the dataset card by:
- Adding the `text-generation` task category to the metadata.
- Adding relevant tags for improved searchability.
- Improving the overall formatting and structure for better readability.
- Adding a more descriptive title.
README.md
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license: mit
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---
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We use Stdio input/output format here. For example, for the task to calculate the sum of a list, the input and output are in the following format:
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```python
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input = "5
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output = "15"
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```
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```
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In this project, we have converted the the functional format to the Stdio format to achieve consistency.
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[Paper](https://arxiv.org/abs/2506.03136) | [Code](https://github.com/Gen-Verse/CURE)
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# Citation
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```
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@article{wang2025cure,
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title={Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning},
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author={Wang, Yinjie and Yang, Ling and Tian, Ye and Shen, Ke and Wang, Mengdi},
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---
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license: mit
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task_categories:
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- text-generation
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tags:
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- code-generation
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- unit-testing
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- reinforcement-learning
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- llm
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---
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# Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning Datasets
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This repository contains datasets used in the CURE framework for co-evolving coding and unit testing capabilities in LLMs. The data is formatted using Stdio input/output.
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**Data Format:**
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For tasks like calculating the sum of a list, the input/output is formatted as follows:
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```python
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input = "5
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1 2 3 4 5
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"
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output = "15"
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```
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Note that some datasets were originally in a functional format (e.g., `assert sum_function([1, 2, 3, 4, 5]) == 15`) and have been converted to the Stdio format for consistency.
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**Datasets Included:**
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- CodeContests
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- LiveBench
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- LiveCodeBench
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- CodeForces
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- MBPP
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- CodeContests_train (training data)
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**Downloading Datasets:**
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Use the following commands to download the datasets:
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```bash
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cd data
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python download_dataset.py --dataset LiveBench # Example: Download LiveBench dataset
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python download_dataset.py --dataset CodeContests_train # Example: Download training data
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```
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[Paper](https://arxiv.org/abs/2506.03136) | [Code](https://github.com/Gen-Verse/CURE)
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# Citation
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```bibtex
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@article{wang2025cure,
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title={Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning},
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author={Wang, Yinjie and Yang, Ling and Tian, Ye and Shen, Ke and Wang, Mengdi},
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