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Yearim Kim

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#natural language process... Preprint Sep 2026

$\mu^2$-Bench: A Multilingual Machine Unlearning Benchmark

Undesired information such as harmful content and private data propagates through Multilingual Large Language Models (LLMs) via direct training and indirect cross-linguistic spread. Multilingual Machine Unlearning (MMU) aims to remove such information, yet its evaluation remains underexplored, leaving unclear whether u...

Kyomin Hwang, Hyeonjin Kim, Hyunho Lee et al. · 0 citations
#artificial intelligence Preprint Aug 2026

When Saying No Makes Better Videos: Designing Dual Gatekeeping for Pedagogically Grounded AI Content Creation

Evaluation of a video authoring pipeline featuring two layers of structured refusal shows that both layers independently improve the same instructional dimensions, suggesting that thoughtful resistance and generative AI are not opposites but partners.

Yearim Kim, In-Chang Baek, Nojun Kwak · 0 citations
#artificial intelligence Preprint Aug 2026

LandingAgent: A Reference-Annotated Dataset and Agentic Generation Framework for Landing Pages

This work proposes LandingAgent, a three-phase agentic framework that profiles the target, constructs a reference-guided wireframe, and refines the page through critique-guided polishing, and evaluates it against direct prompting on faithfulness, conciseness, readability, aesthetics, and structural diversity.

In-Chang Baek, Hyeongseok Lee, Yearim Kim et al. · 0 citations

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