Sunghyun Baek

According to our database, Sunghyun Baek authored at least 9 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Stable-GFlowNet: Toward Diverse and Robust LLM Red-Teaming via Contrastive Trajectory Balance.

Minchan Kwon, Sunghyun Baek, Minseo Kim, Jaemyung Yu, Dongyoon Han, Junmo Kim

CoRR, May, 2026

Forget What Matters, Keep the Rest: Selective Unlearning of Informative Tokens.

Seunghee Koh, Sunghyun Baek, Youngdong Kim, Junmo Kim

CoRR, April, 2026

IWP: Token Pruning as Implicit Weight Pruning in Large Vision Language Models.

Dong-Jae Lee, Sunghyun Baek, Junmo Kim

CoRR, April, 2026

Prior knowledge of layer-specific pruning numbers guarantees effective random pruning at initialization.

Minju Jung, Sunghyun Baek, Yunho Jeon, Junmo Kim

Pattern Anal. Appl., March, 2026

IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation.

Sunghyun Baek, Jaemyung Yu, Seunghee Koh, Minsu Kim, Hyeonseong Jeon, Junmo Kim

CoRR, March, 2026

2025

DAM: Domain-Aware Module for Multi-Domain Dataset Condensation.

Jaehyun Choi, Gyojin Han, Dong-Jae Lee, Sunghyun Baek, Junmo Kim

CoRR, May, 2025

2024

AI-KD: Adversarial learning and Implicit regularization for self-Knowledge Distillation.

Hyungmin Kim, Sungho Suh, Sunghyun Baek, Daehwan Kim, Daun Jeong, Hansang Cho, Junmo Kim

Knowl. Based Syst., 2024

2022

Which Metrics for Network Pruning: Final Accuracy? Or Accuracy Drop?

Donggyu Joo, Sunghyun Baek, Junmo Kim

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

Linearly Replaceable Filters for Deep Network Channel Pruning.

Donggyu Joo, Eojindl Yi, Sunghyun Baek, Junmo Kim

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021