Overview of PAN 2026: Voight-Kampff Generative AI Detection, Text Watermarking, Multi-Author Writing Style Analysis, Generative Plagiarism Detection, and Reasoning Trajectory Detection

Janek Bevendorff, Maik Fröbe, André Greiner-Petter, Andreas Jakoby, Maximilian Mayerl +7 more
2/9/2026
cs.CL

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Abstract

The goal of the PAN workshop is to advance computational stylometry and text forensics via objective and reproducible evaluation. In 2026, we run the following five tasks: (1) Voight-Kampff Generative AI Detection, particularly in mixed and obfuscated authorship scenarios, (2) Text Watermarking, a new task that aims to find new and benchmark the robustness of existing text watermarking schemes, (3) Multi-author Writing Style Analysis, a continued task that aims to find positions of authorship change, (4) Generative Plagiarism Detection, a continued task that targets source retrieval and text alignment between generated text and source documents, and (5) Reasoning Trajectory Detection, a new task that deals with source detection and safety detection of LLM-generated or human-written reasoning trajectories. As in previous years, PAN invites software submissions as easy-to-reproduce Docker containers for most of the tasks. Since PAN 2012, more than 1,100 submissions have been made this way via the TIRA experimentation platform.

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@article{bevendorff2026overview,
  title  = {Overview of PAN 2026: Voight-Kampff Generative AI Detection, Text Watermarking, Multi-Author Writing Style Analysis, Generative Plagiarism Detection, and Reasoning Trajectory Detection},
  author = {Janek Bevendorff and Maik Fröbe and André Greiner-Petter and Andreas Jakoby and Maximilian Mayerl and Preslav Nakov and Henry Plutz and Martin Potthast and Benno Stein and Minh Ngoc Ta and Yuxia Wang and Eva Zangerle},
  year   = {2026},
  eprint = {2602.09147},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2602.09147v1}
}

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