Unsupervised style representations learned via paraphrase inversion enable competitive few-shot and zero-shot AI-text detection with better generalization to unseen LLMs than supervised baselines.
Beat LLM s at Their Own Game: Zero-Shot LLM -Generated Text Detection via Querying C hat GPT
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Steering vectors from frozen LM layers enable a lightweight classifier to detect machine-generated text robustly across domains, source models, and editing attacks.
A distribution-free framework applies knockoff filtering to rewrite-based detectors to achieve finite-sample FDR control for human vs. LLM text detection.
citing papers explorer
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Unsupervised Style Representation Learning for AI-Text Detection via Paraphrase Inversion
Unsupervised style representations learned via paraphrase inversion enable competitive few-shot and zero-shot AI-text detection with better generalization to unseen LLMs than supervised baselines.
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SV-Detect: AI-generated Text Detection with Steering Vectors
Steering vectors from frozen LM layers enable a lightweight classifier to detect machine-generated text robustly across domains, source models, and editing attacks.
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A Distribution-Free Framework for Rewrite-Based Human-text Detection via Knockoff Filtering
A distribution-free framework applies knockoff filtering to rewrite-based detectors to achieve finite-sample FDR control for human vs. LLM text detection.