24 citations · 54 across the 7 of their papers we have counts for
12 papers
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang +7
Large language models (LLMs) have revolutionized natural language processing tasks. However, their practical deployment is hindered by their immense memory and computation requirem…
Real-time Controllable Denoising for Image and Video
Zhaoyang Zhang, Yitong Jiang, Wenqi Shao +4
Controllable image denoising aims to generate clean samples with human perceptual priors and balance sharpness and smoothness. In traditional filter-based denoising methods, this c…
Not All Models Are Equal: Predicting Model Transferability in a Self-challenging Fisher Space
Wenqi Shao, Xun Zhao, Yixiao Ge +5
This paper addresses an important problem of ranking the pre-trained deep neural networks and screening the most transferable ones for downstream tasks. It is challenging because t…
Semantic-preserved Communication System for Highly Efficient Speech Transmission
Tianxiao Han, Qianqian Yang, Zhiguo Shi +2
Deep learning (DL) based semantic communication methods have been explored for the efficient transmission of images, text, and speech in recent years. In contrast to traditional wi…
Dynamic Token Normalization Improves Vision Transformers
Wenqi Shao, Yixiao Ge, Zhaoyang Zhang +4
Vision Transformer (ViT) and its variants (e.g., Swin, PVT) have achieved great success in various computer vision tasks, owing to their capability to learn long-range contextual i…
Differentiable Dynamic Quantization with Mixed Precision and Adaptive Resolution
Zhang Zhaoyang, Shao Wenqi, Gu Jinwei +2
Model quantization is challenging due to many tedious hyper-parameters such as precision (bitwidth), dynamic range (minimum and maximum discrete values) and stepsize (interval betw…