How to Detect AI-Generated Text — Key Takeaways from PAN 2026
- PAN 2026 announced 5 tasks related to AI-generated text detection.
- Two new tasks were added: text watermarking and inference trajectory detection.
- It’s an academic benchmark with over 1,100 submissions since 2012.
5 Tasks Covered by PAN 2026
PAN is a workshop dealing with text forensics. This year, it presented 5 tasks.[arXiv]
The first is Vojt-Kamp AI Detection. It distinguishes between AI-written and human-written text. Detection must be possible even in obfuscated situations.
The second, newly established task is Text Watermarking. It involves embedding invisible markers in AI text and verifying their resistance to attacks.[PAN 2026]
From Author Analysis to Inference Trajectory
The third is Multi-Author Style Analysis. It finds the points where the author changes within a document.
The fourth is Generative Plagiarism Detection. It reverse-traces the original source from text created by AI referencing that source.
The fifth, newly established task is Inference Trajectory Detection. It identifies the source of the LLM’s reasoning process and detects safety issues.[arXiv]
How to Participate and Outlook
Submit your model as a Docker container, and it will be automatically evaluated on the TIRA platform.[PAN]
As AI-generated content surges, the importance of detection technology is also growing. I hope this is helpful for educational institutions and the media industry as well.
Frequently Asked Questions (FAQ)
Q: Can anyone participate in PAN 2026?
A: Yes, not only academic researchers but also industry professionals can participate. Submit your model as a Docker container, and it will be automatically evaluated on TIRA. You only need to register for the CLEF conference, and team participation is also possible.
Q: What is obfuscation in the Vojt-Kamp task?
A: It’s a technique to disguise AI-generated text as if it were written by a human. This includes paraphrasing, style transformation, and word substitution. PAN 2026 requires models that can detect even these types of texts.
Q: What is the principle behind text watermarking?
A: It’s a technology that inserts statistically detectable patterns when AI generates text. It’s invisible to the human eye but detectable by algorithms. Both insertion accuracy and attack robustness are evaluated.
If you found this article helpful, please subscribe to AI Digester.
References
- Overview of PAN 2026 – arXiv (2026-02-09)
- PAN Workshop – Webis Group (2026)
- TIRA Experimentation Platform – TIRA (2026)