Research Scientist · ByteDance Seed

Jing Liu

LLM pre-training & efficient AI

I am a Research Scientist at Seed Model, ByteDance USA, where I work on LLM pre-training.

I received my PhD from Monash University, under the supervision of Prof. Bohan Zhuang and Prof. Jianfei Cai. I am a member of ZIP Lab. Prior to my Ph.D., I completed my master’s degree at South China University of Technology, under the supervision of Prof. Mingkui Tan and Prof. Qingyao Wu.

Apr 30, 2026 Three papers are accepted by ICML 2026!
Sep 18, 2025 One paper is accepted by NeurIPS 2025!
Jun 25, 2025 One paper is accepted by ICCV 2025!
Jan 23, 2025 One paper is accepted by ICLR 2025!
Dec 10, 2024 Two papers are accepted by AAAI 2025!
Sep 26, 2024 Two papers are accepted by NeurIPS 2024!
Jul 01, 2024 One paper is accepted by ECCV 2024!
Feb 27, 2024 Two papers are accepted by CVPR 2024!
Jan 17, 2024 Two papers are accepted by ICLR 2024!
Dec 29, 2023 One paper is accepted by TPAMI!
Sep 22, 2023 One paper is accepted by NeurIPS 2023!
Jul 13, 2023 One paper is accepted by ICCV 2023!
May 13, 2023 One paper is accepted by TPAMI!
Apr 20, 2023 One survey paper is accepted by IJCAI 2023!
Feb 28, 2023 One paper is accepted by CVPR 2023!
Nov 02, 2022 Ecoformer is selected as a spotlight paper!
Sep 15, 2022 One paper is accepted by NeruIPS 2022!

Publications

* indicates equal contributions

Full bibliography

2026

  1. Tech Report
    Seed2.1 Model Card: Agentic Intelligence for Productivity
    ByteDance Seed
    Technical Report, 2026
  2. Tech Report
    Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity
    ByteDance Seed
    arXiv preprint arXiv:2607.00248, 2026
  3. Tech Report
    Seed1.8 Model Card: Towards Generalized Real-World Agency
    ByteDance Seed
    arXiv preprint arXiv:2603.20633, 2026
  4. LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws
    Xu Ouyang ,  Deyi Liu ,  Yuhang Cai ,  Jing Liu ,  Yuan Yang ,  Chen Zheng ,  Thomas Hartvigsen ,  and  Yiyuan Ma
    In International Conference on Machine Learning (ICML) , 2026
  5. INT v.s. FP: A Comprehensive Study of Fine-Grained Low-bit Quantization Formats
    Mengzhao Chen ,  Meng Wu ,  Hui Jin ,  Zhihang Yuan ,  Jing Liu ,  Chaoyi Zhang ,  Yunshui Li ,  Jie Huang ,  Jin Ma ,  Zeyue Xue ,  Zhiheng Liu ,  Xingyan Bin ,  and  Ping Luo
    In International Conference on Machine Learning (ICML) , 2026
  6. Scaling Law for Quantization-Aware Training
    Mengzhao Chen ,  Chaoyi Zhang ,  Jing Liu ,  Yutao Zeng ,  Zeyue Xue ,  Zhiheng Liu ,  Yunshui Li ,  Jin Ma ,  Jie Huang ,  Xun Zhou ,  and  Ping Luo
    In International Conference on Machine Learning (ICML) , 2026

2025

  1. arXiv
    GatePro: Parameter-Free Expert Selection Optimization for Mixture-of-Experts Models
    Chen Zheng ,  Yuhang Cai ,  Deyi Liu ,  Jin Ma ,  Yiyuan Ma ,  Yuan Yang ,  Jing Liu ,  Yutao Zeng ,  Xun Zhou ,  and  Siyuan Qiao
    arXiv preprint arXiv:2510.13079, 2025
  2. arXiv
    Balanced Actor Initialization: Stable RLHF Training of Distillation-Based Reasoning Models
    Chen Zheng ,  Yiyuan Ma ,  Yuan Yang ,  Deyi Liu ,  Jing Liu ,  Zuquan Song ,  Yuxin Song ,  Cheng Ren ,  Hang Zhu ,  Xin Liu ,  Yiyuan Ma ,  Siyuan Qiao ,  Xun Zhou ,  Liang Xiang ,  and  Yonghui Wu
    arXiv preprint arXiv:2509.00309, 2025
  3. Model Merging in Pre-training of Large Language Models
    Yunshui Li ,  Yiyuan Ma ,  Shen Yan ,  Chaoyi Zhang ,  Jing Liu ,  Jianqiao Lu ,  Ziwen Xu ,  Mengzhao Chen ,  Minrui Wang ,  Shiyi Zhan ,  Jin Ma ,  Xunhao Lai ,  Yao Luo ,  Xingyan Bin ,  Hongbin Ren ,  Mingji Han ,  Wenhao Hao ,  Bairen Yi ,  LingJun Liu ,  Bole Ma ,  Xiaoying Jia ,  Zhou Xun ,  Liang Xiang ,  and  Yonghui Wu
    In Conference on Neural Information Processing Systems (NeurIPS) , 2025
  4. ZipVL: Accelerating Vision-Language Models through Dynamic Token Sparsity
    Yefei He ,  Feng Chen ,  Jing Liu ,  Wenqi Shao ,  Hong Zhou ,  Kaipeng Zhang ,  and  Bohan Zhuang
    In International Conference on Computer Vision (ICCV) , 2025
  5. Channel Merging: Preserving Specialization for Merged Experts
    Mingyang Zhang ,  Jing Liu ,  Ganggui Ding ,  Linlin Ou ,  Xinyi Yu ,  and  Bohan Zhuang
    In AAAI Conference on Artificial Intelligence (AAAI) , 2025
  6. Numerical Pruning for Efficient Autoregressive Models
    Xuan Shen ,  Zhao Song ,  Yufa Zhou ,  Bo Chen ,  Jing Liu ,  Ruiyi Zhang ,  Ryan A Rossi ,  Hao Tan ,  Tong Yu ,  Xiang Chen ,  Yufan Zhou ,  Tong Sun ,  Pu Zhao ,  Yanzhi Wang ,  and  Jiuxiang Gu
    In AAAI Conference on Artificial Intelligence (AAAI) , 2025

2024

  1. MiniCache: KV Cache Compression in Depth Dimension for Large Language Models
    Akide Liu ,  Jing Liu ,  Zizheng Pan ,  Yefei He ,  Gholamreza Haffari ,  and  Bohan Zhuang
    In Conference on Neural Information Processing Systems (NeurIPS) , 2024
  2. ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification
    Yefei He ,  Luoming Zhang ,  Weijia Wu ,  Jing Liu ,  Hong Zhou ,  and  Bohan Zhuang
    In Conference on Neural Information Processing Systems (NeurIPS) , 2024
  3. Stitched ViTs are Flexible Vision Backbones
    Zizheng Pan ,  Jing Liu ,  Haoyu He ,  Jianfei Cai ,  and  Bohan Zhuang
    In European Conference on Computer Vision (ECCV) , 2024
  4. Efficient Stitchable Task Adaptation
    Haoyu He ,  Zizheng Pan ,  Jing Liu ,  Jianfei Cai ,  and  Bohan Zhuang
    In Conference on Computer Vision and Pattern Recognition (CVPR) , 2024
  5. CVPR Highlight
    Tfmq-dm: Temporal feature maintenance quantization for diffusion models
    Yushi Huang* ,  Ruihao Gong* ,  Jing Liu ,  Tianlong Chen ,  and  Xianglong Liu
    In Conference on Computer Vision and Pattern Recognition (CVPR) , 2024
    Spotlight (top 11% of the accepted papers)
  6. QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models
    Jing Liu ,  Ruihao Gong ,  Xiuying Wei ,  Zhiwei Dong ,  Jianfei Cai ,  and  Bohan Zhuang
    In International Conference on Learning Representations (ICLR) , 2024
  7. ICLR Spotlight
    EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models
    Yefei He ,  Jing Liu ,  Weijia Wu ,  Hong Zhou ,  and  Bohan Zhuang
    In International Conference on Learning Representations (ICLR) , 2024
    Spotlight (top 5% of the accepted papers)

2023

  1. Pruning self-attentions into convolutional layers in single path
    Haoyu He ,  Jing Liu ,  Zizheng Pan ,  Jianfei Cai ,  Jing Zhang ,  Dacheng Tao ,  and  Bohan Zhuang
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
  2. PTQD: Accurate Post-Training Quantization for Diffusion Models
    Yefei He ,  Luping Liu ,  Jing Liu ,  Weijia Wu ,  Hong Zhou ,  and  Bohan Zhuang
    In Conference on Neural Information Processing Systems (NeurIPS) , 2023
  3. BiViT: Extremely Compressed Binary Vision Transformers
    Yefei He ,  Zhenyu Lou ,  Luoming Zhang ,  Jing Liu ,  Weijia Wu ,  Hong Zhou ,  and  Bohan Zhuang
    In International Conference on Computer Vision (ICCV) , 2023
  4. Single-path bit sharing for automatic loss-aware model compression
    Jing Liu ,  Bohan Zhuang ,  Peng Chen ,  Chunhua Shen ,  Jianfei Cai ,  and  Mingkui Tan
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
  5. A Survey on Efficient Training of Transformers
    Bohan Zhuang ,  Jing Liu ,  Zizheng Pan ,  Haoyu He ,  Yuetian Weng ,  and  Chunhua Shen
    In International Joint Conference on Artificial Intelligence (IJCAI) , 2023
    Survey Track
  6. Dynamic Focus-Aware Positional Queries for Semantic Segmentation
    Haoyu He ,  Jianfei Cai ,  Zizheng Pan ,  Jing Liu ,  Jing Zhang ,  Dacheng Tao ,  and  Bohan Zhuang
    In Conference on Computer Vision and Pattern Recognition (CVPR) , 2023

2022

  1. NeurIPS Spotlight
    EcoFormer: Energy-Saving Attention with Linear Complexity
    Jing Liu* ,  Zizheng Pan* ,  Haoyu He ,  Jianfei Cai ,  and  Bohan Zhuang
    In Conference on Neural Information Processing Systems (NeurIPS) , 2022
    Spotlight (top 5% of the accepted papers)
  2. Less is more: Pay less attention in vision transformers
    Zizheng Pan ,  Bohan Zhuang ,  Haoyu He ,  Jing Liu ,  and  Jianfei Cai
    In AAAI Conference on Artificial Intelligence (AAAI) , 2022

2021

  1. Scalable Vision Transformers With Hierarchical Pooling
    Zizheng Pan ,  Bohan Zhuang ,  Jing Liu ,  Haoyu He ,  and  Jianfei Cai
    In International Conference on Computer Vision (ICCV) , 2021
  2. arXiv
    Sharpness-aware quantization for deep neural networks
    Jing Liu ,  Jianfei Cai ,  and  Bohan Zhuang
    arXiv preprint arXiv:2111.12273, 2021
  3. arXiv
    Mesa: A memory-saving training framework for transformers
    Zizheng Pan ,  Peng Chen ,  Haoyu He ,  Jing Liu ,  Jianfei Cai ,  and  Bohan Zhuang
    arXiv preprint arXiv:2111.11124, 2021
  4. Discrimination-aware network pruning for deep model compression
    Jing Liu* ,  Bohan Zhuang* ,  Zhuangwei Zhuang* ,  Yong Guo ,  Junzhou Huang ,  Jinhui Zhu ,  and  Mingkui Tan*
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
  5. Effective training of convolutional neural networks with low-bitwidth weights and activations
    Bohan Zhuang* ,  Mingkui Tan* ,  Jing Liu* ,  Lingqiao Liu ,  Ian Reid ,  and  Chunhua Shen
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
  6. CVPR Oral
    AQD: Towards Accurate Quantized Object Detection
    Peng Chen* ,  Jing Liu* ,  Bohan Zhuang ,  Mingkui Tan ,  and  Chunhua Shen
    In Conference on Computer Vision and Pattern Recognition (CVPR) , 2021
    Oral Presentation (top 4% of the accepted papers)

2020

  1. Deep transferring quantization
    Zheng Xie* ,  Zhiquan Wen* ,  Jing Liu* ,  Zhiqiang Liu ,  Xixian Wu ,  and  Mingkui Tan
    In European Conference on Computer Vision (ECCV) , 2020
  2. Generative low-bitwidth data free quantization
    Shoukai Xu* ,  Haokun Li* ,  Bohan Zhuang* ,  Jing Liu ,  Jiezhang Cao ,  Chuangrun Liang ,  and  Mingkui Tan
    In European Conference on Computer Vision (ECCV) , 2020

2018

  1. Discrimination-aware Channel Pruning for Deep Neural Networks
    Zhuangwei Zhuang* ,  Mingkui Tan* ,  Bohan Zhuang* ,  Jing Liu* ,  Yong Guo ,  Qingyao Wu ,  Junzhou Huang ,  and  Jinhui Zhu
    In Conference on Neural Information Processing Systems (NeurIPS) , 2018