AI Text Detection
Team DACTYL's PAN 2026 submission combines Bayesian data mixing and empirical cross-risk minimization to build more robust AI-generated text detectors, tackling generalization across unseen generators and domains.
AI Text Detection
New research introduces Exons-Detect, which identifies AI-generated text by analyzing hidden-state discrepancies in exonic tokens—key linguistic markers that differ between human and machine writing.
LLM watermarking
Researchers introduce WaterMod, a modular token-rank partitioning approach that improves LLM watermarking by maintaining probability balance across model outputs, enhancing detection while preserving text quality.