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Overview of PAN 2024: Multi-author Writing Style Analysis, Multilingual Text Detoxification, Oppositional Thinking Analysis, and Generative AI Authorship Verification Condensed Lab Overview

  • Abinew Ali Ayele,
  • Nikolay Babakov,
  • Janek Bevendorff,
  • Xavier Bonet Casals,
  • Berta Chulvi,
  • Daryna Dementieva,
  • Ashaf Elnagar,
  • Dayne Freitag,
  • Maik Fröbe,
  • Damir Korenčić,
  • Maximilian Mayerl,
  • Daniil Moskovskiy,
  • Animesh Mukherjee,
  • Alexander Panchenko,
  • Martin Potthast,
  • Francisco Rangel,
  • Naquee Rizwan,
  • Paolo Rosso,
  • Florian Schneider,
  • Alisa Smirnova,
  • Efstathios Stamatatos,
  • Elisei Stakovskii,
  • Benno Stein,
  • Mariona Taulé,
  • Dmitry Ustalov,
  • Xintong Wang,
  • Matti Wiegmann,
  • Seid Muhie Yimam,
  • Eva Zangerle

摘要

The goal of the PAN lab is to advance the state of the art in text forensics and stylometry through an objective evaluation of new and established methods on new benchmark datasets. IN 2024, we organized four shared tasks: (1) multi-author writing style analysis, which we continue from 2023; (2) multilingual text detoxification, a new task that aims to re-formulate text in a non-toxic way for multiple languages; (3) oppositional thinking analysis, a new task that aims to discriminate critical thinking from conspiracy narratives and identify their core actors; and (4) generative AI authorship verification, which formulates the detection of AI-generated text as an authorship problem. PAN 2024 concluded as one of our most successful editions with 74 notebook papers by 147 participating teams.