AI Detection
PAN 2026 announces five research challenges targeting generative AI detection, text watermarking, multi-author analysis, plagiarism detection, and reasoning trajectory identification.
AI Detection
New research introduces cognitive calibration methods to improve human detection of LLM-generated Korean text, shifting from intuition to expertise-based assessment.
AI Detection
New research uncovers the linguistic patterns that enable AI-generated text detectors to generalize across different language models, offering insights for more robust synthetic content detection.
deepfake fraud
Despite fears of sophisticated AI-powered fraud, deepfake tools are proving less effective than criminals anticipated. New analysis reveals the gap between hype and reality in synthetic media attacks.
Explainable AI
New research combines deep neural networks with Answer Set Programming to generate human-readable explanations for AI decisions, advancing interpretability crucial for detection systems.
deepfakes
Fabricated AI-generated images depicting Venezuelan President Maduro's arrest highlight growing concerns about synthetic media's role in political disinformation and public trust.
voice cloning
Resemble AI CEO Zohaib Ahmed discusses the evolving landscape of voice cloning technology, AI-generated audio authenticity, and the company's approach to responsible synthetic voice development.
AI Detection
New research tackles the challenge of attributing AI-generated content to specific models while handling unknown generators—critical for deepfake detection and digital authenticity verification.
AI Detection
Research reveals significant limitations in human ability to detect AI-generated images, raising critical questions about synthetic media verification and the future of visual authenticity.
AI Detection
New research reveals academic journals' AI usage policies have had minimal impact on the surge of AI-assisted writing in scholarly publications, raising questions about detection effectiveness.
forensic linguistics
New research examines how large language models are transforming forensic linguistics, creating both powerful detection tools and unprecedented challenges for authorship attribution and AI text identification.
AI Detection
New research reveals linguistic markers that distinguish LLM-generated fake news sites from human journalism, offering robust detection methods against adversarial manipulation.