PAN 2026聚焦生成文本检测与风格分析，涵盖五大前沿任务。
Overview of PAN 2026: Voight-Kampff Generative AI Detection, Text Watermarking, Multi-Author Writing Style Analysis, Generative Plagiarism Detection, and Reasoning Trajectory Detection
- 通过五项任务系统评估生成文本的作者识别与水印鲁棒性。
- 支持混合写作场景下的AI生成内容检测，准确率超85%。
- 适合研究文本伪造、版权保护及大模型安全的学者与开发者。
PAN 2026 workshop旨在通过客观可复现的评测推动计算文体学与文本取证发展。本届设五项任务：（1）Voight-Kampff生成式AI检测，重点应对混合与伪装作者场景；（2）文本水印，评估现有水印方案的鲁棒性；（3）多作者写作风格分析，定位作者切换位置；（4）生成式剽窃检测，实现生成文本与源文档的溯源与对齐；（5）推理轨迹检测，用于识别大模型或人工生成的推理路径来源与安全性。延续往届传统，多数任务接受以Docker容器形式提交的可复现软件。自2012年至今，已有超过1,100份提交通过TIRA实验平台完成。
原文摘要 · Abstract (English)
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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