Chaofan Tao

According to our database, Chaofan Tao authored at least 22 papers between 2019 and 2024.

Collaborative distances:

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

2024

FAT: Frequency-Aware Transformation for Bridging Full-Precision and Low-Precision Deep Representations.

Chaofan Tao, Rui Lin, Quan Chen, Zhaoyang Zhang, Ping Luo, Ngai Wong

IEEE Trans. Neural Networks Learn. Syst., February, 2024

Electrocardiogram Instruction Tuning for Report Generation.

Zhongwei Wan, Che Liu, Xin Wang, Chaofan Tao, Hui Shen, Zhenwu Peng, Jie Fu, Rossella Arcucci, Huaxiu Yao, Mi Zhang

CoRR, 2024

RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis.

Yao Mu, Junting Chen, Qinglong Zhang, Shoufa Chen, Qiaojun Yu, Chongjian Ge, Runjian Chen, Zhixuan Liang, Mengkang Hu, Chaofan Tao, Peize Sun, Haibao Yu, Chao Yang, Wenqi Shao, Wenhai Wang, Jifeng Dai, Yu Qiao, Mingyu Ding, Ping Luo

CoRR, 2024

2023

A Spectral Perspective towards Understanding and Improving Adversarial Robustness.

Binxiao Huang, Rui Lin, Chaofan Tao, Ngai Wong

CoRR, 2023

CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers.

Dachuan Shi, Chaofan Tao, Anyi Rao, Zhendong Yang, Chun Yuan, Jiaqi Wang

CoRR, 2023

DyBit: Dynamic Bit-Precision Numbers for Efficient Quantized Neural Network Inference.

Jiajun Zhou, Jiajun Wu, Yizhao Gao, Yuhao Ding, Chaofan Tao, Boyu Li, Fengbin Tu, Kwang-Ting Cheng, Hayden Kwok-Hay So, Ngai Wong

CoRR, 2023

UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers.

Dachuan Shi, Chaofan Tao, Ying Jin, Zhendong Yang, Chun Yuan, Jiaqi Wang

Proceedings of the International Conference on Machine Learning, 2023

Structured Pruning for Efficient Generative Pre-trained Language Models.

Chaofan Tao, Lu Hou, Haoli Bai, Jiansheng Wei, Xin Jiang, Qun Liu, Ping Luo, Ngai Wong

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Frequency Regularization for Improving Adversarial Robustness.

Binxiao Huang, Chaofan Tao, Rui Lin, Ngai Wong

CoRR, 2022

What Do Adversarially trained Neural Networks Focus: A Fourier Domain-based Study.

Binxiao Huang, Chaofan Tao, Rui Lin, Ngai Wong

CoRR, 2022

ODG-Q: Robust Quantization via Online Domain Generalization.

Chaofan Tao, Ngai Wong

Proceedings of the 26th International Conference on Pattern Recognition, 2022

LiteVL: Efficient Video-Language Learning with Enhanced Spatial-Temporal Modeling.

Dongsheng Chen, Chaofan Tao, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Compression of Generative Pre-trained Language Models via Quantization.

Chaofan Tao, Lu Hou, Wei Zhang, Lifeng Shang, Xin Jiang, Qun Liu, Ping Luo, Ngai Wong

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

A case-based interpretable deep learning model for classification of mass lesions in digital mammography.

Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin

Nat. Mach. Intell., 2021

Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning.

Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin

CoRR, 2021

IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography.

Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin

CoRR, 2021

FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware Transformation.

Chaofan Tao, Rui Lin, Quan Chen, Zhaoyang Zhang, Ping Luo, Ngai Wong

CoRR, 2021

LiteGT: Efficient and Lightweight Graph Transformers.

Cong Chen, Chaofan Tao, Ngai Wong

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

BATMANN: A Binarized-All-Through Memory-Augmented Neural Network for Efficient In-Memory Computing.

Yuan Ren, Rui Lin, Jie Ran, Chang Liu, Chaofan Tao, Zhongrui Wang, Can Li, Ngai Wong

Proceedings of the 14th IEEE International Conference on ASIC, 2021

2020

Dynamic and Static Context-Aware LSTM for Multi-agent Motion Prediction.

Chaofan Tao, Qinhong Jiang, Lixin Duan, Ping Luo

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

MiniMax Entropy Network: Learning Category-Invariant Features for Domain Adaptation.

Chaofan Tao, Fengmao Lv, Lixin Duan, Min Wu

CoRR, 2019

MR-NET: Exploiting Mutual Relation for Visual Relationship Detection.

Yi Bin, Yang Yang, Chaofan Tao, Zi Huang, Jingjing Li, Heng Tao Shen

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019