3 papers
cs.CV2025
LRQ-DiT: Log-Rotation Post-Training Quantization of Diffusion Transformers for Image and Video Generation
Lianwei Yang, Haokun Lin, Tianchen Zhao +6
Diffusion Transformers (DiTs) have achieved impressive performance in text-to-image and text-to-video generation. However, their high computational cost and large parameter sizes p…
cs.CV2025
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.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…