| 2025 | ICML | GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance. | Jinuk Kim, Marwa El Halabi, Wonpyo Park, Clemens J. S. Schaefer, Deokjae Lee, Yeonhong Park, Jae W. Lee, Hyun Oh Song |
| 2024 | ICLR | Compressed Context Memory for Online Language Model Interaction. | Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun, Hyun Oh Song |
| 2024 | ICML | LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging. | Jinuk Kim, Marwa El Halabi, Mingi Ji, Hyun Oh Song |
| 2024 | ICML | Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization. | Deokjae Lee, Hyun Oh Song, Kyunghyun Cho |
| 2023 | ACL | Query-Efficient Black-Box Red Teaming via Bayesian Optimization. | Deokjae Lee, JunYeong Lee, Jung-Woo Ha, Jin-Hwa Kim, Sang-Woo Lee, Hwaran Lee, Hyun Oh Song |
| 2023 | ICML | Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming. | Jinuk Kim, Yeonwoo Jeong, Deokjae Lee, Hyun Oh Song |
| 2022 | AAAI | Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks. | Seungyong Moon, Gaon An, Hyun Oh Song |
| 2022 | AISTATS | Optimal channel selection with discrete QCQP. | Yeonwoo Jeong, Deokjae Lee, Gaon An, Changyong Son, Hyun Oh Song |
| 2022 | ICML | Dataset Condensation via Efficient Synthetic-Data Parameterization. | Jang-Hyun Kim, Jinuk Kim, Seong Joon Oh, Sangdoo Yun, Hwanjun Song, Joonhyun Jeong, Jung-Woo Ha, Hyun Oh Song |
| 2022 | ICML | Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization. | Deokjae Lee, Seungyong Moon, Junhyeok Lee, Hyun Oh Song |
| 2021 | ICLR | Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity. | Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song |
| 2020 | ICML | Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup. | Jang-Hyun Kim, Wonho Choo, Hyun Oh Song |
| 2019 | CVPR | End-To-End Efficient Representation Learning via Cascading Combinatorial Optimization. | Yeonwoo Jeong, Yoonsung Kim, Hyun Oh Song |
| 2019 | ICML | Learning Discrete and Continuous Factors of Data via Alternating Disentanglement. | Yeonwoo Jeong, Hyun Oh Song |
| 2019 | ICML | EMI: Exploration with Mutual Information. | Hyoungseok Kim, Jaekyeom Kim, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song |
| 2019 | ICML | Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization. | Seungyong Moon, Gaon An, Hyun Oh Song |
| 2018 | ICML | Efficient end-to-end learning for quantizable representations. | Yeonwoo Jeong, Hyun Oh Song |
| 2017 | CVPR | Deep Metric Learning via Facility Location. | Hyun Oh Song, Stefanie Jegelka, Vivek Rathod, Kevin Murphy |
| 2016 | CVPR | Deep Metric Learning via Lifted Structured Feature Embedding. | Hyun Oh Song, Yu Xiang, Stefanie Jegelka, Silvio Savarese |
| 2014 | ICML | On learning to localize objects with minimal supervision. | Hyun Oh Song, Ross B. Girshick, Stefanie Jegelka, Julien Mairal, Zad Harchaoui, Trevor Darrell |
| 2013 | ICML | Discriminatively Activated Sparselets. | Ross B. Girshick, Hyun Oh Song, Trevor Darrell |
| 2012 | ECCV | Sparselet Models for Efficient Multiclass Object Detection. | Hyun Oh Song, Stefan Zickler, Tim Althoff, Ross B. Girshick, Mario Fritz, Christopher Geyer, Pedro F. Felzenszwalb, Trevor Darrell |