Modern dataset search platforms employ ML task-based utility metrics ins...
Zero-shot medical image classification is a critical process in real-wor...
In computer-assisted orthodontics, three-dimensional tooth models are
re...
Recent data search platforms use ML task-based utility measures rather t...
Although dominant for tabular data, ML libraries that train tree models ...
Task-agnostic knowledge distillation attempts to address the problem of
...
Differential privacy (DP) allows data analysts to query databases that
c...
Recent progress in diffusion models has revolutionized the popular techn...
Estimated time of arrival (ETA) prediction, also known as travel time
es...
As a new programming paradigm, deep neural networks (DNNs) have been
inc...
Neural retrievers based on pre-trained language models (PLMs), such as
d...
A critical step in virtual dental treatment planning is to accurately
de...
Pre-trained language models have achieved state-of-the-art results in va...
Differentially private training algorithms provide protection against on...
Pre-trained models have achieved state-of-the-art results in various Nat...
Retrieval is a crucial stage in web search that identifies a small set o...
Pretrained language models (PLMs) such as BERT adopt a training paradigm...
This letter presents a novel framework termed DistSTN for the task of
sy...
This paper describes Galileo's performance in SemEval-2020 Task 12 on
de...
This paper describes the system designed by ERNIE Team which achieved th...
Code switching is a linguistic phenomenon that may occur within a
multil...