Abstract
This paper provides an overview of the 2022 COLING Scholarly Document Processing workshop shared task on the detection of automatically generated scientific papers. We frame the detection problem as a binary classification task: given an excerpt of text, label it as either human-written or machine-generated. We shared a dataset containing excerpts from human-written papers as well as artificially generated content and suspicious documents collected by Elsevier publishing and editorial teams. As a test set, the participants were provided with a 5x larger corpus of openly accessible human-written as well as generated papers from the same scientific domains of documents. The shared task saw 180 submissions across 14 participating teams and resulted in two published technical reports. We discuss our findings from the shared task in this overview paper.
| Original language | English |
|---|---|
| Pages (from-to) | 210-213 |
| Number of pages | 4 |
| Journal | Proceedings - International Conference on Computational Linguistics, COLING |
| Volume | 29 |
| Issue number | 9 |
| State | Published - 2022 |
| Externally published | Yes |
| Event | 3rd Workshop on Scholarly Document Processing, SDP 2022 at 29th International Conference on Computational Linguistics, COLING 2022 - Gyeongju, Korea, Republic of Duration: Oct 12 2022 → Oct 17 2022 |