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

TL;DR

The PAN 2026 workshop presents five tasks to evaluate and improve AI detection, watermarking, authorship analysis, plagiarism detection, and reasoning safety in text and AI-generated content.

Contribution

It introduces new tasks like Voight-Kampff AI detection, text watermarking robustness, and reasoning trajectory detection, expanding the scope of computational text forensics.

Findings

Development of benchmark datasets for each task.

Evaluation of existing watermarking schemes' robustness.

Baseline results for AI detection and reasoning safety.

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.