3 accepted papers
Distributed training methods are crucial for large language models (LLMs). However, existing distributed training methods often suffer from communication bottlenecks, stragglers, and limited elasticity, particularly in heterogeneous or large-scale environments. Local SGD methods have been proposed t…
Dynamic NeRFs have recently been used for 3D talking portrait synthesis, but challenges remain in improving efficiency and effectiveness. We introduce R2-Talker, an efficient and effective framework for real-time talking head synthesis. Using multi-resolution hash grids, we losslessly encode facial…
Adaptive optimizers, such as Adam, have achieved remarkable success in deep learning. A key component of these optimizers is the so-called preconditioning matrix, providing enhanced gradient information and regulating the step size of each gradient direction. In this paper, we propose a novel approa…