Authorship Verification

Authorship verification aims to determine if two text samples share the same author, a task with applications in forensics, plagiarism detection, and online security. Current research focuses on improving accuracy and explainability using large language models (LLMs), ensemble learning methods, and novel approaches like contrastive learning and self-supervised learning, often incorporating stylistic features and addressing challenges like topic leakage and adversarial attacks. These advancements are significant for enhancing the reliability and interpretability of authorship analysis across diverse text types, including code, handwritten documents, and online communications.