collaborators

9 papers

cs.CV2026

Toward Trustworthy Portrait Editing: Evaluation of Demographic Misrepresentation in I2I Models

Huichan Seo, Minki Hong, Sieun Choi +2

Instruction-guided image-to-image (I2I) editors are increasingly used in consumer and professional visual workflows, where trustworthiness depends not only on prompt compliance but…

cs.CV2026

Exposing Blindspots: Cultural Bias Evaluation in Generative Image Models

Huichan Seo, Sieun Choi, Minki Hong +8

Generative image models produce striking visuals yet often misrepresent culture. Prior work has examined cultural bias mainly in text-to-image (T2I) systems, leaving image-to-image…

cs.CV2026

StableSketcher: Enhancing Diffusion Model for Pixel-based Sketch Generation via Visual Question Answering Feedback

Jiho Park, Sieun Choi, Jaeyoon Seo +1

Although recent advancements in diffusion models have significantly enriched the quality of generated images, challenges remain in synthesizing pixel-based human-drawn sketches, a…

cs.CL2026

PEEM: Prompt Engineering Evaluation Metrics for Interpretable Joint Evaluation of Prompts and Responses

Minki Hong, Eunsoo Lee, Sohyun Park +1

Prompt design is a primary control interface for large language models (LLMs), yet standard evaluations largely reduce performance to answer correctness, obscuring why a prompt suc…

cs.AI2026

Before We Trust Them: Decision-Making Failures in Navigation of Foundation Models

Jua Han, Jaeyoon Seo, Jungbin Min +4

High success rates on navigation-related tasks do not necessarily translate into reliable decision making by foundation models. To examine this gap, we evaluate current models on s…

cs.CV2026

SEA: Evaluating Sketch Abstraction Efficiency via Element-level Commonsense Visual Question Answering

Jiho Park, Sieun Choi, Jaeyoon Seo +3

A sketch is a distilled form of visual abstraction that conveys core concepts through simplified yet purposeful strokes while omitting extraneous detail. Despite its expressive pow…