Authorship Obfuscation

Authorship obfuscation aims to modify text to conceal the author's identity while preserving meaning, posing a significant challenge to authorship attribution techniques. Current research focuses on developing robust obfuscation methods using large and small language models, often employing techniques like style transfer, reinforcement learning, and constrained decoding to achieve a balance between privacy and text utility. This area is crucial for protecting author anonymity in various contexts, from online reviews to scientific publications, and its advancement necessitates ongoing investigation into the adversarial relationship between obfuscation and attribution methods.