Assessing Deanonymization Risks with Stylometry-Assisted LLM Agent

arXiv:2602.23079v1 Announce Type: new Abstract: The rapid advancement of large language models (LLMs) has enabled powerful authorship inference capabilities, raising growing concerns about unintended deanonymization …