52 citations · 59 across the 7 of their papers we have counts for
8 papers
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…
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…
EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models
Xuewen Liu, Zhikai Li, Junrui Xiao +3
Diffusion models have achieved great success in image generation tasks. However, the lengthy denoising process and complex neural networks hinder their low-latency applications in…
Patch-wise Mixed-Precision Quantization of Vision Transformer
Junrui Xiao, Zhikai Li, Lianwei Yang +1
As emerging hardware begins to support mixed bit-width arithmetic computation, mixed-precision quantization is widely used to reduce the complexity of neural networks. However, Vis…
BinaryViT: Towards Efficient and Accurate Binary Vision Transformers
Junrui Xiao, Zhikai Li, Lianwei Yang +1
Vision Transformers (ViTs) have emerged as the fundamental architecture for most computer vision fields, but the considerable memory and computation costs hinders their application…
RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers
Zhikai Li, Junrui Xiao, Lianwei Yang +1
Post-training quantization (PTQ), which only requires a tiny dataset for calibration without end-to-end retraining, is a light and practical model compression technique. Recently,…
PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers
Zhikai Li, Mengjuan Chen, Junrui Xiao +1
Data-free quantization can potentially address data privacy and security concerns in model compression, and thus has been widely investigated. Recently, PSAQ-ViT designs a relative…
Patch Similarity Aware Data-Free Quantization for Vision Transformers
Zhikai Li, Liping Ma, Mengjuan Chen +2
Vision transformers have recently gained great success on various computer vision tasks; nevertheless, their high model complexity makes it challenging to deploy on resource-constr…