As the size of large language models (LLMs) continues to grow, model
com...
In the era of large-scale language models, the substantial parameter siz...
We present a hardware-efficient architecture of convolutional neural net...
The YOLO community has been in high spirits since our first two releases...
The tradeoff between performance and inference speed is critical for
pra...
Structured pruning greatly eases the deployment of large neural networks...
For years, the YOLO series has been the de facto industry-level standard...
We present a simple yet effective fully convolutional one-stage 3D objec...
Neural architecture search (NAS) has been an active direction of automat...
Most recent methods used for crowd counting are based on the convolution...
Very recently, a variety of vision transformer architectures for dense
p...
Almost all visual transformers such as ViT or DeiT rely on predefined
po...
Recent unsupervised contrastive representation learning follows a Single...
Single-path based differentiable neural architecture search has great
st...
Smart audio devices are gated by an always-on lightweight keyword spotti...
Despite the fast development of differentiable architecture search (DART...
Simplicity is the ultimate sophistication. Differentiable Architecture S...
The expressiveness of search space is a key concern in neural architectu...
Convolutional neural networks are widely adopted in Acoustic Scene
Class...
Differential Architecture Search (DARTS) is now a widely disseminated
we...
One-shot neural architecture search features fast training of a supernet...
The evolution of MobileNets has laid a solid foundation for neural netwo...
The ability to rank models by its real strength is the key to Neural
Arc...
In recent years, deep learning methods have achieved impressive results ...
Deep convolution neural networks demonstrate impressive results in
super...
Fabricating neural models for a wide range of mobile devices demands for...
Non-dominated sorting genetic algorithm II (NSGA-II) does well in dealin...
This paper proposes a first order gradient reinforcement learning algori...
Deep reinforcement learning for multi-agent cooperation and competition ...