4 citations · 5 across the 5 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.LG2024
TTAQ: Towards Stable Post-training Quantization in Continuous Domain Adaptation
Junrui Xiao, Zhikai Li, Lianwei Yang +2
Post-training quantization (PTQ) reduces excessive hardware cost by quantizing full-precision models into lower bit representations on a tiny calibration set, without retraining. D…
cs.CV2024★ 1 cited
DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers
Lianwei Yang, Haisong Gong, Haokun Lin +4
Vision Transformers (ViTs) have gained significant attention, but their high computing cost limits the practical applications. While post-training quantization (PTQ) reduces model…
cs.CV2024
MGRQ: Post-Training Quantization For Vision Transformer With Mixed Granularity Reconstruction
Lianwei Yang, Zhikai Li, Junrui Xiao +2
Post-training quantization (PTQ) efficiently compresses vision models, but unfortunately, it accompanies a certain degree of accuracy degradation. Reconstruction methods aim to enh…