用ELECTRA和风格特征检测中英文学术论文是否由机器生成
IntegrityAI at GenAI Detection Task 2: Detecting Machine-Generated Academic Essays in English and Arabic Using ELECTRA and Stylometry
- 结合ELECTRA模型与文本风格特征，分别训练中英文检测模型
- 英文任务F1达99.7%（排名第二），阿拉伯文98.4%（排名第一）
- 适合关注AI生成内容检测的教育与出版领域研究者
近期研究关注学术用途下机器生成论文的检测问题。本研究采用在中英文学术论文上微调的预训练Transformer模型，并融合风格特征进行检测。针对英语和阿拉伯语分别构建基于ELECTRA和AraELECTRA的定制模型，在基准数据集上进行训练与评估。所提模型在英文子任务中F1分数达到99.7%，位列26支参赛团队第2；阿拉伯语文本检测中取得98.4%的F1分数，位居23支队伍首位。
原文摘要 · Abstract (English)
Recent research has investigated the problem of detecting machine-generated essays for academic purposes. To address this challenge, this research utilizes pre-trained, transformer-based models fine-tuned on Arabic and English academic essays with stylometric features. Custom models based on ELECTRA for English and AraELECTRA for Arabic were trained and evaluated using a benchmark dataset. Proposed models achieved excellent results with an F1-score of 99.7%, ranking 2nd among of 26 teams in the English subtask, and 98.4%, finishing 1st out of 23 teams in the Arabic one.
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