261 citations · 286 across the 5 of their papers we have counts for
5 papers
Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Large Vision-Language Models
Chengcheng Wang, Jianyuan Guo, Hongguang Li +4
Rotary Position Embedding (RoPE) is widely adopted in large language models, but when applied to vision-language models (VLMs) it couples text and image position indices and can in…
Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism
Chengcheng Wang, Wei He, Ying Nie +4
In the past years, YOLO-series models have emerged as the leading approaches in the area of real-time object detection. Many studies pushed up the baseline to a higher level by mod…
Redistribution of Weights and Activations for AdderNet Quantization
Ying Nie, Kai Han, Haikang Diao +3
Adder Neural Network (AdderNet) provides a new way for developing energy-efficient neural networks by replacing the expensive multiplications in convolution with cheaper additions…
Dynamic Resolution Network
Mingjian Zhu, Kai Han, Enhua Wu +4
Deep convolutional neural networks (CNNs) are often of sophisticated design with numerous learnable parameters for the accuracy reason. To alleviate the expensive costs of deployin…
GhostSR: Learning Ghost Features for Efficient Image Super-Resolution
Ying Nie, Kai Han, Zhenhua Liu +2
Modern single image super-resolution (SISR) system based on convolutional neural networks (CNNs) achieves fancy performance while requires huge computational costs. The problem on…