Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
social_media
License:
File size: 1,544 Bytes
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---
license: apache-2.0
task_categories:
- text-classification
language:
- en
tags:
- social_media
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).
Checkout 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 cite the original paper if you use this dataset for your study. Thanks!
```
@article{geigle:2021:arxiv,
author = {Gregor Geigle and
Nils Reimers and
Andreas R{\"u}ckl{\'e} and
Iryna Gurevych},
title = {TWEAC: Transformer with Extendable QA Agent Classifiers},
journal = {arXiv preprint},
volume = {abs/2104.07081},
year = {2021},
url = {http://arxiv.org/abs/2104.07081},
archivePrefix = {arXiv},
eprint = {2104.07081}
}
@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}
}
``` |