GitHub

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

Large language models (LLMs) show excellent performance but are compute- and memory-intensive. Quantization can reduce memory and accelerate inference. However, for LLMs beyond 100 billion parameters, ...
GitHub

isl-org/lang-seg

This project will no longer be maintained by Intel. Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project.
IEEE

IEEE Communications Surveys and Tutorials

Abstract: I welcome you to the fourth issue of the IEEE Communications Surveys and Tutorials in 2021. This issue includes 23 papers covering different aspects of communication networks. In particular, ...
IEEE

Vision-Language Models for Vision Tasks: A Survey

Abstract: Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to ...