Training and deploying the large language models requires a large mount of computational
resource because the language models contain billions of parameters and the text has …

Large language models have made significant progress in the past few years. However,
they are either generic {\it or} field specific, splitting the community into different groups. In …

The yield surface of a material is a criterion at which macroscopic plastic deformation
begins. For crystalline solids, plastic deformation occurs through the motion of dislocations …

Diffusion models are getting popular in generative image and video synthesis. However,
due to the diffusion process, they require a large number of steps to converge. To tackle this …

The denoising task of low-dose CT images is a highly complex and uncertain inverse
problem. Previous studies have primarily relied on convolutional neural network to reduce …

Activation functions play an essential role in neural networks. They provide the non-linearity
for the networks. Therefore, their properties are important for neural networks' accuracy and …

Inspired by Federated Learning, in this paper, we propose personal large models that are
distilled from traditional large language models but more adaptive to local users' personal …

Although there are many iterative solvers for total variation models, few attention has been
paid on the fast and effective approximation to their optimal solutions. In this paper, we …

Activation functions are essential components of neural networks. In this paper, we introduce
a new activation function called the Truncated and Signed Square Root (TSSR) function …

Although the anisotropic Gaussian kernels in 3D Gaussian splatting methods are effective in
representing the geometry, their arbitrary orientation causes several optimization difficulties …