PAN'25/26 Generative AI Detection: Voight-Kampff AI Detection Sensitivity

This is the dataset for the Voight-Kampff Generative AI Authorship Verification shared tasks PAN@CLEF2025 (Subtask 1) and PAN@CLEF2026. Please consult the tasks' pages for further details on the format, the dataset's creation, and links to baselines and utility code. Task 2025 Subtask 1 is a binary AI detection task in that participants are given a text and have to decide whether it was machine-authored (class 1) or human-authored (class 0). However, we introduced a twist: The LLMs were instructed to change their style and mimic a specific human author. Furthermore, the test set will contain several surprises such as new models or unknown obfuscations to test the robustness of the classifiers (however, texts will be from the same domain). As in the previous year, the Voight-Kampff AI detection Task @ PAN is organized in collaboration with the Voight-Kampff Task @ ELOQUENT Lab Lab in a builder-breaker style. PAN participants will build systems to tell human and machine apart, while ELOQUENT participants will investigate novel text generation and obfuscation methods for avoiding detection. Task 2026 The 2026 shared task reuses the same training data, but will be evaluated on different test data to further challenge the out-of-domain classification effectiveness of the detectors.