"LRQuant+: A Unified and Learnable Framework to Post-Training Quantization ..."

Jiaqi Zhao et al. (2025)

> Home

Details and statistics

DOI: 10.1109/TPAMI.2025.3599479

access: closed

type: Journal Article

metadata version: 2025-11-16

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/pami/ZhaoZWHSZN25
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/pami/ZhaoZWHSZN25
Jiaqi Zhao, Chao Zeng, Ming Wang, Linxuan Han, Yuzhang Shang, Miao Zhang, Liqiang Nie:
LRQuant+: A Unified and Learnable Framework to Post-Training Quantization for Transformer-Based Large Foundation Models. IEEE Trans. Pattern Anal. Mach. Intell. 47(12): 11817-11833 (2025)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.