6 papers
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…
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…
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…
VisDoT : Enhancing Visual Reasoning through Human-Like Interpretation Grounding and Decomposition of Thought
Eunsoo Lee, Jeongwoo Lee, Minki Hong +2
Large vision-language models (LVLMs) struggle to reliably detect visual primitives in charts and align them with semantic representations, which severely limits their performance o…
NormGenesis: Multicultural Dialogue Generation via Exemplar-Guided Social Norm Modeling and Violation Recovery
Minki Hong, Jangho Choi, Jihie Kim
Social norms govern culturally appropriate behavior in communication, enabling dialogue systems to produce responses that are not only coherent but also socially acceptable. We pre…
Systematic Integration of Attention Modules into CNNs for Accurate and Generalizable Medical Image Diagnosis
Zahid Ullah, Minki Hong, Tahir Mahmood +1
Deep learning has become a powerful tool for medical image analysis; however, conventional Convolutional Neural Networks (CNNs) often fail to capture the fine-grained and complex f…