SOURCE-LINKED INTELLIGENCE
Detecting and Guiding LLM-Generated Korean Poetry with Interpretable Form-level Features
LLMs often struggle with modern Korean poetry, producing outputs that resemble "line-broken prose." We address two coupled tasks: detecting whether a Korean poem is human- or LLM-authored, and guiding LLMs to generate poetry closer in form to human writing. We quantify the human-LLM gap along four form-level linguistic dimensions: output length (Volume), the diversity and connective use of line-final forms (Structure Variation), the irregularity of line lengths (Rhythmic Irregularity), and adherence to standard orthography (Normative Adherence). We operationalize these dimensions as five inter
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-29T01:45:50.000Z
First collected: 2026-09-21T07:51:58.603Z. This is not the publication date.