1 citations · 2 across the 11 of their papers we have counts for
5 papers · 1 filter
Linguistics-Aware Non-Distortionary LLM Watermarking
Shinwoo Park, Hyejin Park, Hyeseon An +1
Watermarking should identify language-model output without degrading quality or limiting verification to the model provider. Multilingual deployment makes this harder because morph…
When LLM Essays Outscore Student Essays: What a Korean Writing Rubric Rewards and Where Readers Disagree
Shinwoo Park, Yo-Sub Han
LLMs now help students plan, draft, and revise essays. Educational assessment therefore faces a basic question: how should student and LLM writing be compared? Rubrics assign point…
Steering Language Models Before They Speak: Logit-Level Interventions
Hyeseon An, Shinwoo Park, Hyundong Jin +1
Controllable generation requires language models to realize output characteristics such as reading level, politeness, and toxicity. Existing steering methods are often indirect, re…
A Linguistics-Aware LLM Watermarking via Syntactic Predictability
Shinwoo Park, Hyejin Park, Hyeseon An +1
As large language models (LLMs) continue to advance rapidly, reliable governance tools have become critical. Publicly verifiable watermarking is particularly essential for fosterin…
KatFishNet: Detecting LLM-Generated Korean Text through Linguistic Feature Analysis
Shinwoo Park, Shubin Kim, Do-Kyung Kim +1
The rapid advancement of large language models (LLMs) increases the difficulty of distinguishing between human-written and LLM-generated text. Detecting LLM-generated text is cruci…