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title: README
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<p align="center">
<img src="OpenDataArena.PNG" alt="OpenDataArena Banner" width="400">
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## π About OpenDataArena
**OpenDataArena (ODA)** is an open research initiative devoted to evaluating, benchmarking, and creating high-value datasets for the post-training era of large language models (LLMs).
We believe **data quality defines model capability** β and that **open, reproducible evaluation** is key to accelerating progress in AI.
### π Our Mission
To make **data evaluation scientific, transparent, and community-driven**, while continuously **producing high-value, openly available datasets** that enhance model alignment and reasoning ability.
### π Key Features
- π **Dataset Leaderboard** β [Leaderboard](https://opendataarena.github.io/leaderboard.html) ranks and visualizes the most valuable datasets across multiple domains, based on unified post-training benchmarks.
- π **Comprehensive Scoring System** β [Scoring tool](https://github.com/OpenDataArena/OpenDataArena-Tool/tree/main/data_scorer) measures dataset quality, diversity, difficulty, and learning value using reproducible pipelines.
- π§° **Open-Source Toolkit** β *[OpenDataArena-Tool](https://github.com/OpenDataArena/OpenDataArena-Tool)* enables dataset curation, scoring, and analysis with a standardized, community-driven workflow.
- π± **High-Value Data Generation** β beyond evaluation, ODA continuously produces and shares new, top-quality datasets for fine-tuning and alignment research.
If you find our work helpful, please consider β **starring** and **subscribing** to support open, data-driven AI research. Learn more at [opendataarena.github.io](https://opendataarena.github.io). |