📚 BlendNet

The dataset contains $12k$ samples. To balance cost savings with data quality and scale, we manually annotated $2k$ samples and used GPT-4o to annotate the remaining $10k$ samples.

For more details, please visit our GitHub repository or refer to our arXiv paper.

📖 Citation

@misc{du2024blenderllmtraininglargelanguage,
      title={BlenderLLM: Training Large Language Models for Computer-Aided Design with Self-improvement}, 
      author={Yuhao Du and Shunian Chen and Wenbo Zan and Peizhao Li and Mingxuan Wang and Dingjie Song and Bo Li and Yan Hu and Benyou Wang},
      year={2024},
      eprint={2412.14203},
      archivePrefix={arXiv},
      primaryClass={cs.HC},
      url={https://arxiv.org/abs/2412.14203}, 
}

We are from the School of Data Science (SDS), the Chinese University of Hong Kong, Shenzhen (CUHKSZ).