Authorship Attribution

Authorship attribution aims to identify the author of a text, a task with applications ranging from forensic linguistics to plagiarism detection and the verification of AI-generated content. Current research focuses on improving the accuracy and robustness of attribution methods across diverse genres and languages, employing techniques like transformer-based models, recurrent neural networks (RNNs), and ensemble learning, while also addressing challenges such as topic leakage and the explainability of model predictions. These advancements have significant implications for various fields, including digital forensics, literary studies, and the detection of misinformation generated by large language models.