| 2026 | ASPLOS | A Cost-Effective Near-Storage Processing Solution for Offline Inference of Long-Context LLMs. | Hongsun Jang, Jaeyong Song, Changmin Shin, Si Ung Noh, Jaewon Jung, Jisung Park, Jinho Lee |
| 2025 | NAACL | LLM-guided Plan and Retrieval: A Strategic Alignment for Interpretable User Satisfaction Estimation in Dialogue. | Sangyeop Kim, Sohhyung Park, Jaewon Jung, Jinseok Kim, Sungzoon Cho |
| 2024 | CVPR | PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor. | Jaewon Jung, Hongsun Jang, Jaeyong Song, Jinho Lee |
| 2024 | DATE | Pipette: Automatic Fine-Grained Large Language Model Training Configurator for Real-World Clusters. | Jinkyu Yim, Jaeyong Song, Yerim Choi, Jaebeen Lee, Jaewon Jung, Hongsun Jang, Jinho Lee |
| 2024 | HPCA | Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System. | Hongsun Jang, Jaeyong Song, Jaewon Jung, Jaeyoung Park, Youngsok Kim, Jinho Lee |
| 2023 | ASPLOS | Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression. | Jaeyong Song, Jinkyu Yim, Jaewon Jung, Hongsun Jang, Hyung-Jin Kim, Youngsok Kim, Jinho Lee |
| 2023 | DAC | Fast Adversarial Training with Dynamic Batch-level Attack Control. | Jaewon Jung, Jaeyong Song, Hongsun Jang, Hyeyoon Lee, Kanghyun Choi, Noseong Park, Jinho Lee |
| 2023 | DATE | Pipe-BD: Pipelined Parallel Blockwise Distillation. | Hongsun Jang, Jaewon Jung, Jaeyong Song, Joonsang Yu, Youngsok Kim, Jinho Lee |
| 2017 | VEHITS | Validation and Control Strategy to Reduce Fuel Consumption for RE-EV. | Wonbin Lee, Wonseok Choi, Hyunjong Ha, Jiho Yoo, Junbeom Wi, Jaewon Jung, Hyunsoo Kim |