Author

In-Chang Baek

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Preprint Oct 2026

RobotUse: Allocating Computation, Context, and Decisions

Robot agents must connect their intended actions to observed outcomes while retaining the context needed to revise their choices over repeated attempts. Existing interfaces often leave these choices inside predefined tools or require agents to manage detailed execution code and its growing history. We introduce RobotUs...

Junhoo Lee, In-Chang Baek, Seungyeon Kim 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