Biography and Contact

I am a final-year Ph.D. student of Faculty Information Technology at Monash University, Australia. 

I am supervised by Asst. Prof. Bohan Zhuang, Prof. Jianfei Cai, and Prof. Chunhua Shen.

My main research topic is efficient AI.

Here is my CV and google scholar. 

Github: https://github.com/liujingcs.

Email: liujing_95@outlook.com. 

News

• 2024.01: Two papers are accepted by ICLR!

• 2023.09: One paper is accepted by NeurIPS!

• 2023.07: One paper is accepted by ICCV!

• 2023.05: One paper is accepted by TPAMI!

• 2023.04: One survey paper is accepted by IJCAI 2023!

• 2023.03: One paper is accepted by CVPR 2023!

• 2022.11: Ecoformer will be presented as Spotlight!

• 2022.09: One first-author paper is accepted by NeruIPS 2022!

Publications

(* indicates equal contributions)

• QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models

Jing Liu, Ruihao Gong, Xiuying Wei, Zhiwei Dong, Jianfei Cai, Bohan Zhuang

International Conference on Learning Representations (ICLR), 2024

[arxiv]

• EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models

Yefei He, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang

International Conference on Learning Representations (ICLR Spotlight), 2024

[arxiv]

• PTQD: Accurate Post-Training Quantization for Diffusion Models

Yefei He, Luping Liu, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang

Neural Information Processing Systems (NeurIPS), 2023

[arxiv]

• BiViT: Extremely Compressed Binary Vision Transformers

Yefei He, Lou Zhenyu, Luoming Zhang, Jing Liu, Weijia Wu, Bohan Zhuang, Hong Zhou

International Conference on Computer Vision (ICCV), 2023

[arxiv]

• Single-path Bit Sharing for Automatic Loss-aware Model Compression

Jing Liu, Bohan Zhuang, Peng Chen, Chunhua Shen, Jianfei Cai, Mingkui Tan

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023

[arxiv]

• A Survey on Efficient Training of Transformers

Bohan Zhuang, Jing Liu, Zizheng Pan, Haoyu He, Yuetian Weng, Chunhua Shen

International Joint Conference on Artificial Intelligence (IJCAI), 2023

[arxiv]

• Dynamic Focus-aware Positional Queries for Semantic Segmentation

Haoyu He, Jianfei Cai, Zizheng Pan, Jing Liu, Jing Zhang, Dacheng Tao, Bohan Zhuang

Conference on Computer Vision and Pattern Recognition (CVPR), 2023

[arxiv][code]

• EcoFormer: Energy-Saving Attention with Linear Complexity

Jing Liu, Zizheng Pan*, Haoyu He, Jianfei Cai, Bohan Zhuang

Neural Information Processing Systems (NeurIPS Spotlight), 2022

[arxiv][code]

• Sharpness-aware Quantization for Deep Neural Networks

Jing Liu, Jianfei Cai, Bohan Zhuang

[arxiv][code]

• Pruning Self-attentions into Convolutional Layers in Single Path

Haoyu He, Jing Liu, Zizheng Pan, Jianfei Cai, Jing Zhang, Dacheng Tao, Bohan Zhuang

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023

[arxiv][code]

• Mesa: A Memory-saving Training Framework for Transformers

Zizheng Pan, Peng Chen, Haoyu He, Jing Liu, Jianfei Cai, Bohan Zhuang

[arxiv][code]

• Elastic Architecture Search for Diverse Tasks with Different Resources

Jing Liu, Bohan Zhuang, Mingkui Tan, Xu Liu, Dinh Phung, Yuanqing Li, Jianfei Cai

[arxiv]

• Less is More: PayLess Attentionin VisionTransformers

Zizheng Pan, Bohan Zhuang, Haoyu He, Jing Liu, Jianfei Cai

AAAI Conference on Artificial Intelligence (AAAI), 2022

[arxiv][code]

• Scalable Visual Transformers with Hierarchical Pooling

Zizheng Pan, Bohan Zhuang, Jing Liu, Haoyu He, Jianfei Cai

International Conference on Computer Vision (ICCV), 2021

[arxiv][code]

• Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations 

Bohan Zhuang*, Mingkui Tan*, Jing Liu*, Lingqiao Liu, Ian Reid, Chunhua Shen

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021

[arxiv] [code] 

• Discrimination-aware Network Pruning for Deep Model Compression

Jing Liu*, Bohan Zhuang*, Zhuangwei Zhuang*, Yong Guo, Junzhou Huang, Jinhui Zhu, Mingkui Tan

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021

[paper][code]

• AQD: Towards Accurate Quantized Object Detection

Peng Chen, Jing Liu*, Bohan Zhuang, Mingkui Tan, Chunhua Shen

Conference on Computer Vision and Pattern Recognition (CVPR Oral), 2021

[arxiv][code]

• Deep Transferring Quantization

Zheng Xie*, Zhiquan Wen*, Jing Liu*, Zhiqiang Liu, Xixian Wu, Mingkui Tan

European Conference on Computer Vision (ECCV), 2020

[paper][code]

• Generative Low-bitwidth Data Free Quantization

Shoukai Xu*, Haokun Li*, Bohan Zhuang*, Jing Liu, Jiezhang Cao, Chuangrun Liang, Mingkui Tan 

European Conference on Computer Vision (ECCV), 2020

[paper][code]

• Discrimination-aware Channel Pruning for Deep Neural Networks

Zhuangwei Zhuang*, Mingkui Tan*, Bohan Zhuang*, Jing Liu*, Yong Guo, Qingyao Wu, Junzhou Huang, Jinhui Zhu

Neural Information Processing Systems (NeurIPS), 2018 

[paper][code]

Professional Services

• Conferences: CVPR, ICLR, NeurIPS, ECCV, ICM, MICCAI

• Journals: IJCV, TPAMI, TPAMI

Awards and Scholarships

• NeurIPS 2021 Outstanding Reviewer

• Faculty of Information Technology Research Scholarship

Thanks for your attention !