| 2026 | AAAI | Impute Missing Entries with Uncertainty. | Jaesung Lim, Seunghwan An, Jong-June Jeon |
| 2026 | PAKDD | Estimating Subgraph Importance with Structural Prior Domain Knowledge. | Changhyun Kim, Seunghwan An, Jong-June Jeon |
| 2026 | PAKDD | DrIM: Context-Driven Nearest Neighbor Imputation Using Language Representation. | Jaesung Lim, Seunghwan An, Jong-June Jeon |
| 2026 | WSDM | Revisiting IPS in Recommendation Models: Unveiling Its Impact on Model Performance. | Wonhyung Shin, Jong-June Jeon |
| 2025 | AAAI | Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis. | Seunghwan An, Gyeongdong Woo, Jaesung Lim, Chang-Hyun Kim, Sungchul Hong, Jong-June Jeon |
| 2025 | CIKM | Generalizing Query Performance Prediction under Retriever and Concept Shifts via Data-driven Correction. | Jaehwan Jung, Jong-June Jeon |
| 2025 | CIKM | CHEM: Causally and Hierarchically Explaining Molecules. | Gyeongdong Woo, Soyoung Cho, Donghyeon Kim, Kimoon Na, Changhyun Kim, Jinhee Choi, Jong-June Jeon |
| 2025 | IJCAI | Dynamic Higher-Order Relations and Event-Driven Temporal Modeling for Stock Price Forecasting. | Kijeong Park, Sungchul Hong, Jong-June Jeon |
| 2024 | CIKM | Cryptocurrency Price Forecasting using Variational Autoencoder with Versatile Quantile Modeling. | Sungchul Hong, Seunghwan An, Jong-June Jeon |
| 2023 | ECAI | Causally Disentangled Generative Variational AutoEncoder. | Seunghwan An, Kyungwoo Song, Jong-June Jeon |