Update README.md

# Description
- In ad text generation (ATG), desirable ad text is both faithful and informative. That is, it should be faithful to the input document, while at the same time containing important information that appeals to potential customers. The existing evaluation data, [CAMERA (Mita et al.,2024)](https://aclanthology.org/2024.acl-long.54/), is suitable for evaluating informativeness, as it consists of reference ad texts created by ad creators. However, these references often include information unfaithful to the input, which is a notable obstacle in promoting ATG research. Therefore, we collaborate with in-house ad creators to refine the CAMERA references and develop an alternative Japanese ATG evaluation dataset called FaithCAMERA, in which the faithfulness of references is guaranteed.



# Terms of use
- This data set is provided under a [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license.

## References
```
@inproceedings{mita2024striking,
title={Striking Gold in Advertising: Standardization and Exploration of Ad Text Generation},
author={Mita, Masato and Murakami, Soichiro and Kato, Akihiko and Zhang, Peinan},
booktitle={Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
pages={955--972},
year={2024}
}
```

## Citation
If you use this dataset, please cite the following work:

```bibtex


@misc
{kato2024faithcamera,
title={FaithCAMERA: Construction of a Faithful Dataset for Ad Text Generation},
author={Akihiko Kato and Masato Mita and Soichiro Murakami and Ukyo Honda and Sho Hoshino and Peinan Zhang},
year={2024},
eprint={2410.03839},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2410.03839},
}
```

README.md

@@ -18,4 +18,14 @@ configs:
   data_files:
   - split: train
     path: data/train-*
----
+license: cc-by-sa-4.0
+task_categories:
+- text-generation
+language:
+- ja
+tags:
+- faithfulness
+- advertisement_text_generation
+size_categories:
+- 1K<n<10K
+---