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This is the dataset for the shared task on Voight-Kampff Generative AI Authorship Verification PAN@CLEF2025 (Subtask 1). Please consult the task's page for further details on the format, the dataset's creation, and links to baselines and utility code. Task 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.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |