Limitations of Human Identification of Automatically Generated Text: Dataset
<p>This repository contains the data for the paper:</p> <p><span>Nadège Alavoine, Maximin Coavoux, Emmanuelle Esperança-Rodier, Romane Gallienne, Carlos-Emiliano González-Gallardo, Jérôme Goulian, Jose G. Moreno, Aurélie Névéol, Didier Schwab, Vincent Segonne, and Johanna Simoens. 2024. <a href="https://aclanthology.org/2024.lrec-main.919">Limitations of Human Identification of Automatically Generated Text</a>. In <em>Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, pages 10511–10516, Torino, Italia. ELRA and ICCL.</span></p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0