Papers with unsupervised detection framework
Unsupervised Detection of LLM-Generated Text in Korean Using Syntactic and Semantic Cues (2026.findings-eacl)
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| Challenge: | Prior work focused on English, leaving low-resource languages such as Korean underexplored. |
| Approach: | They propose an unsupervised framework that integrates syntactic token cohesiveness and semantic regeneration similarity to detect Korean text. |
| Outcome: | The proposed framework outperforms baselines in Korean and other low-resource languages without training. |