task_categories:text-classification size_categories:10K<n<100K language:en license:apache-2.0 product review topic_classification arxiv:2306.15895 region:us
---
license: apache-2.0
task_categories:
- text-classification
language:
- en
tags:
- product
- review
- topic_classification
size_categories:
- 10K<n<100K
---


This is the data used in the paper [Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias](https://github.com/yueyu1030/AttrPrompt).
Check the paper: https://arxiv.org/abs/2306.15895 for details.

- `label.txt`: the label name for each class
- `train.jsonl`: The original training set.
- `valid.jsonl`: The original validation set.
- `test.jsonl`: The original test set.
- `simprompt.jsonl`: The training data generated by the simple prompt.
- `attrprompt.jsonl`: The training data generated by the attributed prompt.

Please check our original paper for details. Moreover, we provide the generated dataset using LLM as follows:
- `regen.jsonl`: The training data generated by [ReGen](https://github.com/yueyu1030/ReGen).
- `regen_llm_augmented.jsonl`: The training data generated by ReGen, with the subtopics generated by the LLM.
- `progen.jsonl`: The training data generated by [ProGen](https://github.com/hkunlp/progen).



Please cite the original paper if you use this dataset for your study. Thanks!

```
@inproceedings{blitzer2007biographies,
  title={Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification},
  author={Blitzer, John and Dredze, Mark and Pereira, Fernando},
  booktitle={Proceedings of the 45th annual meeting of the association of computational linguistics},
  pages={440--447},
  year={2007}
}

@article{yu2023large,
  title={Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias},
  author={Yu, Yue and Zhuang, Yuchen and Zhang, Jieyu and Meng, Yu and Ratner, Alexander and Krishna, Ranjay and Shen, Jiaming and Zhang, Chao},
  journal={arXiv preprint arXiv:2306.15895},
  year={2023}
}
```