APT-Pipe: A Prompt-Tuning Tool for Social Data Annotation using ChatGPT.
Yiming Zhu|Zhizhuo Yin|Gareth Tyson|Ehsan ul Haq|Lik-Hang Lee|Pan Hui
| Anthology ID: | DBLP:conf/www/ZhuYTHL024 |
|---|---|
| Volume: | Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024 |
| Year: | 2024 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 245-255 |
| URL: | https://doi.org/10.1145/3589334.3645642 |
| DOI: | https://doi.org/10.1145/3589334.3645642 |
| DBLP: | conf/www/ZhuYTHL024 |
| BibTeX: |
@inproceedings{zhu-2024-aptpipe,
author = {Yiming Zhu and
Zhizhuo Yin and
Gareth Tyson and
Ehsan ul Haq and
Lik-Hang Lee and
Pan Hui},
editor = {Tat-Seng Chua and
Chong-Wah Ngo and
Ravi Kumar and
Hady Wirawan Lauw and
Roy Ka-Wei Lee},
title = {{APT-Pipe: A Prompt-Tuning Tool for Social Data Annotation using ChatGPT}},
booktitle = {{Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024}},
pages = {245--255},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3589334.3645642},
doi = {https://doi.org/10.1145/3589334.3645642}
}