Jing Liu

@inproceedings{liu2024minicache,
  title = {MiniCache: KV Cache Compression in Depth Dimension for Large Language Models},
  author = {Liu, Akide and Liu, Jing and Pan, Zizheng and He, Yefei and Haffari, Gholamreza and Zhuang, Bohan},
  booktitle = {Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2024},
}

@inproceedings{he2024zipcache,
  title = {ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification},
  author = {He, Yefei and Zhang, Luoming and Wu, Weijia and Liu, Jing and Zhou, Hong and Zhuang, Bohan},
  booktitle = {Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2024},
}

@inproceedings{pan2023snnetv2,
  title = {Stitched ViTs are Flexible Vision Backbones},
  author = {Pan, Zizheng and Liu, Jing and He, Haoyu and Cai, Jianfei and Zhuang, Bohan},
  booktitle = {European Conference on Computer Vision (ECCV)},
  year = {2024},
}

@inproceedings{he2023efficient,
  title = {Efficient Stitchable Task Adaptation},
  author = {He, Haoyu and Pan, Zizheng and Liu, Jing and Cai, Jianfei and Zhuang, Bohan},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
}

@inproceedings{huang2023tfmq,
  title = {Tfmq-dm: Temporal feature maintenance quantization for diffusion models},
  author = {Huang*, Yushi and Gong*, Ruihao and Liu, Jing and Chen, Tianlong and Liu, Xianglong},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  price = {Highlight},
  long_price = {Spotlight (top 11% of the accepted papers)},
}

@inproceedings{liu2024qllm,
  title = {{QLLM}: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models},
  author = {Liu, Jing and Gong, Ruihao and Wei, Xiuying and Dong, Zhiwei and Cai, Jianfei and Zhuang, Bohan},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
}

@inproceedings{he2024efficientdm,
  title = {Efficient{DM}: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models},
  author = {He, Yefei and Liu, Jing and Wu, Weijia and Zhou, Hong and Zhuang, Bohan},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  price = {Spotlight},
  long_price = {Spotlight (top 5% of the accepted papers)}
}

@article{he2021pruning,
  title = {Pruning self-attentions into convolutional layers in single path},
  author = {He, Haoyu and Liu, Jing and Pan, Zizheng and Cai, Jianfei and Zhang, Jing and Tao, Dacheng and Zhuang, Bohan},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  year = {2023},
}

@inproceedings{he2023ptqd,
  title = {{PTQD}: Accurate Post-Training Quantization for Diffusion Models},
  author = {He, Yefei and Liu, Luping and Liu, Jing and Wu, Weijia and Zhou, Hong and Zhuang, Bohan},
  booktitle = {Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://openreview.net/forum?id=Y3g1PV5R9l},
}

@inproceedings{he2023bivit,
  title = {BiViT: Extremely Compressed Binary Vision Transformers},
  author = {He, Yefei and Lou, Zhenyu and Zhang, Luoming and Liu, Jing and Wu, Weijia and Zhou, Hong and Zhuang, Bohan},
  booktitle = {International Conference on Computer Vision (ICCV)},
  pages = {5651--5663},
  year = {2023},
}

@article{liu2023single,
  title = {Single-path bit sharing for automatic loss-aware model compression},
  author = {Liu, Jing and Zhuang, Bohan and Chen, Peng and Shen, Chunhua and Cai, Jianfei and Tan, Mingkui},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2023},
  doi = {10.1109/TPAMI.2023.3275159}
}

@inproceedings{ijcai2023p764,
  title = {A Survey on Efficient Training of Transformers},
  author = {Zhuang, Bohan and Liu, Jing and Pan, Zizheng and He, Haoyu and Weng, Yuetian and Shen, Chunhua},
  booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},
  pages = {6823--6831},
  year = {2023},
  note = {Survey Track},
  doi = {10.24963/ijcai.2023/764},
}

@inproceedings{He_2023_CVPR,
  author = {He, Haoyu and Cai, Jianfei and Pan, Zizheng and Liu, Jing and Zhang, Jing and Tao, Dacheng and Zhuang, Bohan},
  title = {Dynamic Focus-Aware Positional Queries for Semantic Segmentation},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  pages = {11299-11308},
}

@inproceedings{liu2022ecoformer,
  author = {Liu*, Jing and Pan*, Zizheng and He, Haoyu and Cai, Jianfei and Zhuang, Bohan},
  booktitle = {Conference on Neural Information Processing Systems (NeurIPS)},
  pages = {10295--10308},
  title = {EcoFormer: Energy-Saving Attention with Linear Complexity},
  volume = {35},
  year = {2022},
  price = {Spotlight},
  long_price = {Spotlight (top 5% of the accepted papers)},
}

@inproceedings{pan2022less,
  title = {Less is more: Pay less attention in vision transformers},
  author = {Pan, Zizheng and Zhuang, Bohan and He, Haoyu and Liu, Jing and Cai, Jianfei},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  volume = {36},
  number = {2},
  pages = {2035--2043},
  year = {2022},
}

@inproceedings{Pan_2021_ICCV,
  author = {Pan, Zizheng and Zhuang, Bohan and Liu, Jing and He, Haoyu and Cai, Jianfei},
  title = {Scalable Vision Transformers With Hierarchical Pooling},
  booktitle = {International Conference on Computer Vision (ICCV)},
  year = {2021},
  pages = {377-386},
}

@article{liu2021sharpness,
  title = {Sharpness-aware quantization for deep neural networks},
  author = {Liu, Jing and Cai, Jianfei and Zhuang, Bohan},
  booktitle = {arXiv},
  journal = {arXiv preprint arXiv:2111.12273},
  year = {2021},
}

@article{pan2021mesa,
  title = {Mesa: A memory-saving training framework for transformers},
  author = {Pan, Zizheng and Chen, Peng and He, Haoyu and Liu, Jing and Cai, Jianfei and Zhuang, Bohan},
  journal = {arXiv preprint arXiv:2111.11124},
  year = {2021},
}

@article{liu2021discrimination,
  title = {Discrimination-aware network pruning for deep model compression},
  author = {Liu*, Jing and Zhuang*, Bohan and Zhuang*, Zhuangwei and Guo, Yong and Huang, Junzhou and Zhu, Jinhui and Tan*, Mingkui},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  volume = {44},
  number = {8},
  pages = {4035--4051},
  year = {2021},
}

@article{zhuang2021effective,
  title = {Effective training of convolutional neural networks with low-bitwidth weights and activations},
  author = {Zhuang*, Bohan and Tan*, Mingkui and Liu*, Jing and Liu, Lingqiao and Reid, Ian and Shen, Chunhua},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  volume = {44},
  number = {10},
  pages = {6140--6152},
  year = {2021},
}

@inproceedings{Chen_2021_CVPR,
  author = {Chen*, Peng and Liu*, Jing and Zhuang, Bohan and Tan, Mingkui and Shen, Chunhua},
  title = {AQD: Towards Accurate Quantized Object Detection},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
  pages = {104-113},
  price = {Oral},
  long_price = {Oral Presentation (top 4% of the accepted papers)},
}

@inproceedings{xie2020deep,
  title = {Deep transferring quantization},
  author = {Xie*, Zheng and Wen*, Zhiquan and Liu*, Jing and Liu, Zhiqiang and Wu, Xixian and Tan, Mingkui},
  booktitle = {European Conference on Computer Vision (ECCV)},
  pages = {625--642},
  year = {2020},
}

@inproceedings{xu2020generative,
  title = {Generative low-bitwidth data free quantization},
  author = {Xu*, Shoukai and Li*, Haokun and Zhuang*, Bohan and Liu, Jing and Cao, Jiezhang and Liang, Chuangrun and Tan, Mingkui},
  booktitle = {European Conference on Computer Vision (ECCV)},
  pages = {1--17},
  year = {2020},
}

@incollection{zhuang2018discrimination,
  title = {Discrimination-aware Channel Pruning for Deep Neural Networks},
  author = {Zhuang*, Zhuangwei and Tan*, Mingkui and Zhuang*, Bohan and Liu*, Jing and Guo, Yong and Wu, Qingyao and Huang, Junzhou and Zhu, Jinhui},
  booktitle = {Conference on Neural Information Processing Systems (NeurIPS)},
  pages = {881--892},
  year = {2018},
}