Internet Archive Scholar

Artificial Text Detection with Multiple Training Strategies
Обнаружение искусственного текста с несколькими стратегиями обучения

Bin Li, College of Electrical and Information Engineering, Hunan University, Changsha, China, Yixuan Weng, Qiya Song, Hanjun Deng, National Laboratory of Pattern Recognition Institute of Automation, College of Electrical and Information Engineering, Hunan University, Changsha, China, Experimental High School Affiliated to Beijing Normal University, Beijing, China
2022 Computational Linguistics and Intellectual Technologies   unpublished

Preserved Fulltext

fulltext thumbnail
Web Archive Capture PDF (228.2 kB)
https://web.archive.org/web/20221102035721/https://www.dialog-21.ru/media/5777/libplusetal104.pdf

A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL. The file type is application/pdf.

As the deep learning rapidly promote, the artificial texts created by generative models are commonly used in news and social media. However, such models can be abused to generate product reviews, fake news, and even fake political content. The paper proposes a solution for the Russian Artificial Text Detection in the Dialogue shared task 2022 (RuATD 2022) to distinguish which model within the list is used to generate this text. We introduce the DeBERTa pre-trained language model with multiple
more » ... aining strategies for this shared task. Extensive experiments conducted on the RuATD dataset validate the effectiveness of our proposed method. Moreover, our submission ranked second place in the evaluation phase for RuATD 2022 (Multi-Class).
doi:10.28995/2075-7182-2022-20-375-381 fatcat:3d6h4dpzincztgqhc2dfjlbfbq
Citation

Bin Li, College of Electrical and Information Engineering, Hunan University, Changsha, China, Yixuan Weng, Qiya Song, Hanjun Deng, National Laboratory of Pattern Recognition Institute of Automation, College of Electrical and Information Engineering, Hunan University, Changsha, China, Experimental High School Affiliated to Beijing Normal University, Beijing, China. "Artificial Text Detection with Multiple Training Strategies." Computational Linguistics and Intellectual Technologies (2022)