AI Text Detection
A new DeBERTa-based detector tackles AI-generated text under adversarial paraphrasing and realistic deployment conditions, addressing a critical blind spot in synthetic media authentication.
AI Text Detection
A new detection method models text as a graph of sentence transitions, exposing the tell-tale over-regularity of AI-generated writing. The approach flags synthetic prose by measuring how unnaturally smooth its flow of ideas is compared to human text.
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.