787 citations · 3.8k across the 54 of their papers we have counts for
5 papers · 1 filter
MBIR Training for a 2.5D DL network in X-ray CT
Obaidullah Rahman, Madhuri Nagare, Ken D. Sauer +4
In computed tomographic imaging, model based iterative reconstruction methods have generally shown better image quality than the more traditional, faster filtered backprojection te…
GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language Model
Shicheng Tan, Weng Lam Tam, Yuanchun Wang +9
Currently, the reduction in the parameter scale of large-scale pre-trained language models (PLMs) through knowledge distillation has greatly facilitated their widespread deployment…
Are Intermediate Layers and Labels Really Necessary? A General Language Model Distillation Method
Shicheng Tan, Weng Lam Tam, Yuanchun Wang +4
The large scale of pre-trained language models poses a challenge for their deployment on various devices, with a growing emphasis on methods to compress these models, particularly…
Towards Lightweight and Automated Representation Learning System for Networks
Yuyang Xie, Jiezhong Qiu, Laxman Dhulipala +4
We propose LIGHTNE 2.0, a cost-effective, scalable, automated, and high-quality network embedding system that scales to graphs with hundreds of billions of edges on a single machin…
Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and Toolkit
Bo Chen, Jing Zhang, Fanjin Zhang +5
Name disambiguation -- a fundamental problem in online academic systems -- is now facing greater challenges with the increasing growth of research papers. For example, on AMiner, a…