Hsu, Yen-Chang

18 publications

TMLR 2026 ToMoE: Converting Dense Large Language Models to Mixture-of-Experts Through Dynamic Structural Pruning Shangqian Gao, Ting Hua, Reza Shirkavand, Chi-Heng Lin, Zheng Tang, Zhengao Li, Longge Yuan, Fangyi Li, Zeyu Zhang, Alireza Ganjdanesh, Qian Lou, Jie Xu, Yen-Chang Hsu

ICLR 2025 MoDeGPT: Modular Decomposition for Large Language Model Compression Chi-Heng Lin, Shangqian Gao, James Seale Smith, Abhishek Patel, Shikhar Tuli, Yilin Shen, Hongxia Jin, Yen-Chang Hsu

ICML 2025 Retraining-Free Merging of Sparse MoE via Hierarchical Clustering I-Chun Chen, Hsu-Shen Liu, Wei-Fang Sun, Chen-Hao Chao, Yen-Chang Hsu, Chun-Yi Lee

CVPRW 2024 Continual Diffusion with STAMINA: STack-and-Mask INcremental Adapters James Seale Smith, Yen-Chang Hsu, Zsolt Kira, Yilin Shen, Hongxia Jin

TMLR 2024 Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA James Seale Smith, Yen-Chang Hsu, Lingyu Zhang, Ting Hua, Zsolt Kira, Yilin Shen, Hongxia Jin

NeurIPS 2024 DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models Shangqian Gao, Chi-Heng Lin, Ting Hua, Tang Zheng, Yilin Shen, Hongxia Jin, Yen-Chang Hsu

WACV 2024 Token Fusion: Bridging the Gap Between Token Pruning and Token Merging Minchul Kim, Shangqian Gao, Yen-Chang Hsu, Yilin Shen, Hongxia Jin

CVPRW 2023 A Closer Look at Rehearsal-Free Continual Learning James Seale Smith, Junjiao Tian, Shaunak Halbe, Yen-Chang Hsu, Zsolt Kira

NeurIPS 2023 Training Energy-Based Normalizing Flow with Score-Matching Objectives Chen-Hao Chao, Wei-Fang Sun, Yen-Chang Hsu, Zsolt Kira, Chun-Yi Lee

ICLR 2022 DictFormer: Tiny Transformer with Shared Dictionary Qian Lou, Ting Hua, Yen-Chang Hsu, Yilin Shen, Hongxia Jin

ICLR 2022 Language Model Compression with Weighted Low-Rank Factorization Yen-Chang Hsu, Ting Hua, Sungen Chang, Qian Lou, Yilin Shen, Hongxia Jin

CVPR 2022 Lite-MDETR: A Lightweight Multi-Modal Detector Qian Lou, Yen-Chang Hsu, Burak Uzkent, Ting Hua, Yilin Shen, Hongxia Jin

NeurIPS 2021 A Geometric Perspective Towards Neural Calibration via Sensitivity Decomposition Junjiao Tian, Dylan Yung, Yen-Chang Hsu, Zsolt Kira

ICCV 2021 Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning James Smith, Yen-Chang Hsu, Jonathan Balloch, Yilin Shen, Hongxia Jin, Zsolt Kira

NeurIPSW 2021 Exploring Covariate and Concept Shift for Out-of-Distribution Detection Junjiao Tian, Yen-Chang Hsu, Yilin Shen, Hongxia Jin, Zsolt Kira

NeurIPS 2020 Posterior Re-Calibration for Imbalanced Datasets Junjiao Tian, Yen-Cheng Liu, Nathaniel Glaser, Yen-Chang Hsu, Zsolt Kira

ICLR 2019 Multi-Class Classification Without Multi-Class Labels Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser, Phillip Odom, Zsolt Kira

ICLR 2018 Learning to Cluster in Order to Transfer Across Domains and Tasks Yen-Chang Hsu, Zhaoyang Lv, Zsolt Kira