Beyond Surface Cues: Robust LLM-Generated Korean Text Detection

Summary

Researchers introduce KoLing, a bias-controlled adversarial benchmark of 50.9k instances for detecting LLM-generated Korean text, aimed at suppressing superficial shortcuts. They also propose KoLingProbe, an interpretable detector grounded in theoretical linguistics that models Korean-specific properties across multiple linguistic levels. They report that KoLingProbe substantially outperforms strong baselines on all detection tasks and stays robust to adversarial attacks.