collaborators

8 papers

cs.CL2026

FeedEval: Pedagogically Aligned Evaluation of LLM-Generated Essay Feedback

Seongyeub Chu, Jongwoo Kim, Munyong Yi

Going beyond the prediction of numerical scores, recent research in automated essay scoring has increasingly emphasized the generation of high-quality feedback that provides justif…

cs.LG2026

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors

Jeongwhan Choi, Jongwoo Kim, Woosung Kang +1

One of the most challenging problems in graph machine learning is generalizing across graphs with diverse properties. Graph neural networks (GNNs) face a fundamental limitation: th…

cs.CV2026

Leveraging Spatial Context for Positive Pair Sampling in Histopathology Image Representation Learning

Willmer Rafell Quinones Robles, Sakonporn Noree, Jongwoo Kim +3

Deep learning has shown strong potential in cancer classification from whole-slide images (WSIs), but the need for extensive expert annotations often limits its success. Annotation…

cs.AI2026

Aspect-Aware MOOC Recommendation in a Heterogeneous Network

Seongyeub Chu, Jongwoo Kim, Mun Yong Yi

MOOC recommendation systems have received increasing attention to help learners navigate and select preferred learning content. Traditional methods such as collaborative filtering…

cs.LG2025

Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning

Jongwoo Kim, Seongyeub Chu, Hyeongmin Park +3

Recent advancements in graph neural networks (GNNs) and heterogeneous GNNs (HGNNs) have advanced node embeddings and relationship learning for various tasks. However, existing meth…

cs.CV2025

MicroMIL: Graph-Based Multiple Instance Learning for Context-Aware Diagnosis with Microscopic Images

Jongwoo Kim, Bryan Wong, Huazhu Fu +3

Cancer diagnosis has greatly benefited from the integration of whole-slide images (WSIs) with multiple instance learning (MIL), enabling high-resolution analysis of tissue morpholo…