LIU Yijiang (刘一茳), a Ph.D. candidate at Nanjing University, focuses on research areas including on-device large models, model compression and acceleration, as well as software-hardware co-optimization design. He has published multiple papers in CCF-A international top-tier journals and conferences. His first-author paper (AAAI’25 Pruning-Aware Tuning) has been applied to Samsung’s on-device applications for smartphones and TVs. Additionally, his collaborative work with UC Berkeley (ICCV’23 Q-Diffusion) has been featured in MIT OpenCourse and adopted by NVIDIA’s TensorRT team for deployment.
🔥🔥🔥 We are recruiting Master and Ph.D students! Please visit our Lab page for more details! 南京大学智能感知与通信实验室
🔥 News
- 2025.04: 🎉🎉 IJCAI 2025: FBQuant, a novel quantization method for LLMs.
- 2024.12: 🎉🎉 AAAI 2025: PAT, an efficient pruning technology for LLMs.
- 2024.02: 🎉🎉 CVPR 2024: Cloud-Device Collaborative.
- 2024.02: 🎉🎉 CVPR 2024: PromptCoT, a novel technology for enhancing T2I quality.
- 2024.04: 🎉🎉 Q-Diffusion is featured in the newest TensorRT post and MIT opencourses.
- 2023.08: 🎉🎉 Project: LLaMA-Accessory, an Open-source Toolkit for LLM Development.
- 2023.08: 🎉🎉 ICCV 2023: Q-Diffusion, a low-bit quantization technology for diffusion models.
- 2023.03: 🎉🎉 CVPR 2023: NoisyQuant, a novel quantization mothod for Vision Transformers.
📝 Publications
IJCAI 2025 FBQuant: FeedBack Quantization for Large Language Models
Yijiang Liu, Hengyu Fang, Liulu He, Rongyu Zhang, Yichuan Bai, Yuan Du, Li Du
- LLM quantization.
- Sub-branch approach.
AAAI 2025 PAT: Pruning-Aware Tuning for Large Language Models
Yijiang Liu, Huanrui Yang, Youxin Chen, Rongyu Zhang, Miao Wang, Yuan Du, Li Du
- LLM structural pruning.
- Adaptation to downstream tasks.
CVPR 2024 PromptCoT: Align Prompt Distribution via Adapted Chain-of-Thought
Yijiang Liu*, Junyi Yao*, Zhen Dong, Mingfei Guo, Helan Hu, Kurt Keutzer, Li Du, Daquan Zhou, Shanghang Zhang
- Enhance prompt quality by LLMs.
- Enhance T2I generation quality by better prompts.
CVPR 2024 Cloud-Device Collaborative Learning for Multimodal Large Language Models
Guanqun Wang, Jiaming Liu, Chenxuan Li, Yuan Zhang, Junpeng Ma, Xinyu Wei, Kevin Zhang, Maurice Chong, Renrui Zhang, Yijiang Liu, Shanghang Zhang
- Improves compressed MLLMs on devices using cloud-based models.
- Efficient data transmission, knowledge distillation, and adaptive weight compression.
ICCV 2023 Q-diffusion: Quantizing diffusion models
Xiuyu Li, Yijiang Liu, Long Lian, Huanrui Yang, Zhen Dong, Daniel Kang, Shanghang Zhang, Kurt Keutzer
- PTQ method for diffusion models.
- Timestep-aware calibration and shortcut split methods.
CVPR 2023 NoisyQuant: Noisy Bias-Enhanced Post-Training Activation Quantization for Vision Transformers
Yijiang Liu, Huanrui Yang, Zhen Dong, Kurt Keutzer, Li Du, Shanghang Zhang
- Using additive uniform noisy bias to actively reduce quantization error.
- Improving 6-bit quantization performance with minimal overhead.
TIP 2022 Limb Pose Aware Networks for Monocular 3D Pose Estimation
Lele Wu, Zhenbo Yu, Yijiang Liu, Qingshan Liu
- Monocular 3D pose estimation.
- Kinematic constraints and a trajectory-aware approach to reduce estimation errors.
🎖 Services
- Reviewer for CVPR, AAAI, ICML, ACMMM, ICCV, NeurIPS, IJCAI, ICLR.
📖 Educations
- 2022.09 - now, Nanjing University, Ph.D
- 2008.09 - 2012.06, University of Edinburgh, M.S
- 2008.09 - 2012.06, Xidian University, B.S
💬 Invited Talks
- 2025.04, Momenta.
💻 Visitings
- 2022.09 - 2024.12, Peking University.