AI Text Detector

AI text detectors aim to distinguish between human-written and AI-generated text, addressing concerns about plagiarism, misinformation, and academic integrity. Current research focuses on improving the robustness of these detectors against adversarial attacks, such as paraphrasing and back-translation, often employing adversarial learning techniques to enhance their ability to identify manipulated text. The accuracy and reliability of these detectors remain a significant challenge, with ongoing work exploring various model architectures and datasets to improve performance and mitigate the risk of false positives and negatives, impacting fields like education and journalism.