Synthetic Text Detection: Systemic Literature Review
It addresses the need for automated detection algorithms to defend against generated text attacks, but is incremental as it reviews existing literature rather than proposing new methods.
The paper tackles the problem of detecting synthetic text by conducting a systematic literature review to identify current research trends and challenges, aiming to provide a snapshot of the field and lower barriers for future work.
Within the text analysis and processing fields, generated text attacks have been made easier to create than ever before. To combat these attacks open sourcing models and datasets have become a major trend to create automated detection algorithms in defense of authenticity. For this purpose, synthetic text detection has become an increasingly viable topic of research. This review is written for the purpose of creating a snapshot of the state of current literature and easing the barrier to entry for future authors. Towards that goal, we identified few research trends and challenges in this field.