Hung-Yueh Chiang
江泓樂

Selected publications

* Equal contribution

1. 

   Conference ICML

   Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models

   Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin, Kai-Chiang Wu, Mohamed S. Abdelfattah, and Diana Marculescu

   In International Conference on Machine Learning (ICML) 2025

   Bib PDF Code Models Slides Website

   @inproceedings{chiang2025quamba2,
     title = {Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models},
     author = {Chiang, Hung-Yueh and Chang, Chi-Chih and Frumkin, Natalia and Wu, Kai-Chiang and Abdelfattah, Mohamed S. and Marculescu, Diana},
     booktitle = {International Conference on Machine Learning (ICML)},
     year = {2025},
   }

2. 

   Conference ICLR

   Quamba: A Post-Training Quantization Recipe for Selective State Space Models

   Hung-Yueh Chiang*, Chi-Chih Chang*, Natalia Frumkin, Kai-Chiang Wu, and Diana Marculescu

   In International Conference on Learning Representations (ICLR) 2025

   Bib PDF Code Models Talk Demo Website

   @inproceedings{chiang2025quamba,
     title = {Quamba: A Post-Training Quantization Recipe for Selective State Space Models},
     author = {Chiang*, Hung-Yueh and Chang*, Chi-Chih and Frumkin, Natalia and Wu, Kai-Chiang and Marculescu, Diana},
     booktitle = {International Conference on Learning Representations (ICLR)},
     year = {2025},
   }

3. 

   Conference NeurIPS

   Efficient Low-rank Backpropagation for Vision Transformer Adaptation

   Yuedong Yang, Hung-Yueh Chiang, Guihong Li, Diana Marculescu, and Radu Marculescu

   In Advances in Neural Information Processing Systems (NeurIPS) 2023

   Bib PDF Code

   @inproceedings{yang2023efficient,
     title = {Efficient Low-rank Backpropagation for Vision Transformer Adaptation},
     author = {Yang, Yuedong and Chiang, Hung-Yueh and Li, Guihong and Marculescu, Diana and Marculescu, Radu},
     booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
     year = {2023},
   }

4. 

   Conference Oral paper AAAI

   MobileTL: On-device Transfer Learning with Inverted Residual Blocks

   Hung-Yueh Chiang, Natalia Frumkin, Feng Liang, and Diana Marculescu

   In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2023

   Bib PDF Demo Website

   @inproceedings{chiang2022mobiletl,
     title = {MobileTL: On-device Transfer Learning with Inverted Residual Blocks},
     author = {Chiang, Hung-Yueh and Frumkin, Natalia and Liang, Feng and Marculescu, Diana},
     booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)},
     year = {2023},
   }

5. 

   arXiv

   Learning from 2D: Pixel-to-Point Knowledge Transfer for 3D Pretraining

   Yueh-Cheng Liu, Yu-Kai Huang, Hung-Yueh Chiang, Hung-Ting Su, Zhe-Yu Liu, Chin-Tang Chen, Ching-Yu Tseng, and Winston H Hsu

   arXiv preprint arXiv:2104.04687 2021

   Bib PDF

   @article{liu2021learning,
     title = {Learning from 2D: Pixel-to-Point Knowledge Transfer for 3D Pretraining},
     author = {Liu, Yueh-Cheng and Huang, Yu-Kai and Chiang, Hung-Yueh and Su, Hung-Ting and Liu, Zhe-Yu and Chen, Chin-Tang and Tseng, Ching-Yu and Hsu, Winston H},
     journal = {arXiv preprint arXiv:2104.04687},
     year = {2021},
   }

6. 

   Conference 3DV

   A unified point-based framework for 3d segmentation

   Hung-Yueh Chiang, Yen-Liang Lin, Yueh-Cheng Liu, and Winston H Hsu

   In International Conference on 3D Vision (3DV) 2019

   Bib PDF Code Talk Demo Website

   @inproceedings{chiang2019unified,
     title = {A unified point-based framework for 3d segmentation},
     author = {Chiang, Hung-Yueh and Lin, Yen-Liang and Liu, Yueh-Cheng and Hsu, Winston H},
     booktitle = {International Conference on 3D Vision (3DV)},
     year = {2019},
     organization = {IEEE},
   }