| 2025 | CVPR | Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition. | Zheda Mai, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Quang-Huy Nguyen, Li Zhang, Wei-Lun Chao |
| 2024 | CIKM | Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs. | Vardaan Pahuja, Weidi Luo, Yu Gu, Cheng-Hao Tu, Hong-You Chen, Tanya Y. Berger-Wolf, Charles V. Stewart, Song Gao, Wei-Lun Chao, Yu Su |
| 2023 | AAAI | Learning Fractals by Gradient Descent. | Cheng-Hao Tu, Hong-You Chen, David Carlyn, Wei-Lun Chao |
| 2023 | CVPR | Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning. | Cheng-Hao Tu, Zheda Mai, Wei-Lun Chao |
| 2023 | ICLR | On the Importance and Applicability of Pre-Training for Federated Learning. | Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han-Wei Shen, Wei-Lun Chao |
| 2021 | INDIN | Defect Detection Using Deep Lifelong Learning. | Chien-Hung Chen, Cheng-Hao Tu, Jia-Da Li, Chu-Song Chen |
| 2020 | IJCNN | Pruning Depthwise Separable Convolutions for MobileNet Compression. | Cheng-Hao Tu, Jia-Hong Lee, Yi-Ming Chan, Chu-Song Chen |
| 2019 | CVPR | Adaptive Labeling for Deep Learning to Hash. | Huei-Fang Yang, Cheng-Hao Tu, Chu-Song Chen |
| 2019 | ICIP | Adaptive Labeling For Hash Code Learning Via Neural Networks. | Huei-Fang Yang, Cheng-Hao Tu, Chu-Song Chen |