6 papers
Style as a Confound: False Positives in AI Detection of Non-Native Academic Writing
Hyeonchu Park, Gahye Jeong, Bugeun Kim
AI text detectors are increasingly employed in academic settings, but it remains unclear whether their outputs reflect AI authorship itself or broader linguistic features associate…
Relational Over-Regularization: Graph-Based AI-Generated Text Detection via Sentence Transition Deviation
Hyeonchu Park, Bugeun Kim
Detecting AI-generated text (AIGT) remains challenging because existing approaches rely on token-level statistical signals or independent stylometric features, causing them to over…
Diagnosing the Reliability of LLM-as-a-Judge via Item Response Theory
Junhyuk Choi, Sohhyung Park, Chanhee Cho +2
While LLM-as-a-Judge is widely used in automated evaluation, existing validation practices primarily operate at the level of observed outputs, offering limited insight into whether…
Pay What LLM Wants: Can LLM Simulate Economics Experiment with 522 Real-human Persona?
Junhyuk Choi, Hyeonchu Park, Haemin Lee +3
Recent advances in Large Language Models (LLMs) have generated significant interest in their capacity to simulate human-like behaviors, yet most studies rely on fictional personas…
PHISH in MESH: Korean Adversarial Phonetic Substitution and Phonetic-Semantic Feature Integration Defense
Byungjun Kim, Minju Kim, Hyeonchu Park +1
As malicious users increasingly employ phonetic substitution to evade hate speech detection, researchers have investigated such strategies. However, two key challenges remain. Firs…
DART: An AIGT Detector using AMR of Rephrased Text
Hyeonchu Park, Byungjun Kim, Bugeun Kim
As large language models (LLMs) generate more human-like texts, concerns about the side effects of AI-generated texts (AIGT) have grown. So, researchers have developed methods for…