Auto86%Harbor: pendingSafety & AlignmentMultilingual

KoLing

KoLing: A bias-controlled adversarial benchmark for Korean LLM-text detection

KoLing is a 50.9k-instance benchmark for detecting LLM-generated and modified Korean text across essays, abstracts, and editorials, controlling for surface shortcuts.

How to run

ltb · koling
$ npm i -g lettokenburn-cli
$ ltb bench info koling

External harness. No Harbor adapter has been generated for this benchmark yet. `ltb bench info` prints the known links.

Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs

Scores

11 sourced entries
HarnessSourceConfidenceLink
Binoculars66.4N/AIndependentmediumOct 16, 2026arxiv.org
NPR62.7N/AIndependentmediumOct 16, 2026arxiv.org
Fast-DetectGPT62.2N/AIndependentmediumOct 16, 2026arxiv.org
DetectGPT60.3N/AIndependentmediumOct 16, 2026arxiv.org
LLM-Det58.7N/AIndependentmediumOct 16, 2026arxiv.org
Log-Rank56.2N/AIndependentmediumOct 16, 2026arxiv.org
Log-Likelihood55.8N/AIndependentmediumOct 16, 2026arxiv.org
Rank54.8N/AIndependentmediumOct 16, 2026arxiv.org
LRR54.0N/AIndependentmediumOct 16, 2026arxiv.org
GECScore53.4N/AIndependentmediumOct 16, 2026arxiv.org
Entropy53.0N/AIndependentmediumOct 16, 2026arxiv.org

Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.

Reproduced by the community

All runs
Loading community runs…

About

KoLing comprises 50.9k instances of human-written, LLM-modified, and LLM-generated Korean text across three domains. It employs strict shortcut control to eliminate length and punctuation biases.

The benchmark evaluates binary and ternary detection performance. Experiments show that existing detectors rely on superficial cues, while the proposed KoLingProbe achieves robust performance using linguistic features.