AI Generated Text Detection

AI-generated text detection aims to distinguish between human-written and machine-generated text, addressing concerns about misinformation, plagiarism, and other malicious uses of large language models (LLMs). Current research focuses on developing robust detection methods using various approaches, including machine learning classifiers (e.g., BERT, XGBoost, SVM), convolutional neural networks analyzing visual representations of text embeddings, and ensemble methods combining multiple models. The accurate and reliable detection of AI-generated text is crucial for maintaining academic integrity, combating the spread of disinformation, and ensuring the trustworthiness of online information.