Pre-trained models have achieved success in Chinese Short Text Matching ...
In the field of parallel imaging (PI), alongside image-domain regulariza...
Consistency regularization methods, such as R-Drop (Liang et al., 2021) ...
Brain tissue segmentation is essential for neuroscience and clinical stu...
In this paper, a dynamic dual-graph fusion convolutional network is prop...
Multilingual sentence representations are the foundation for similarity-...
The multilingual neural machine translation (NMT) model has a promising
...
MRI and PET are crucial diagnostic tools for brain diseases, as they pro...
Magnetic resonance imaging (MRI) is known to have reduced signal-to-nois...
Recent cross-lingual cross-modal works attempt to extend Vision-Language...
Recently, the practical deployment of open-domain dialogue systems has b...
Recent progress in diffusion models has revolutionized the popular techn...
Physics-Informed Neural Networks (PINNs) have become a kind of attractiv...
Derivative-free prompt learning has emerged as a lightweight alternative...
Recent years have witnessed the rise and success of pre-training techniq...
Recent Vision-Language Pre-trained (VLP) models based on dual encoder ha...
Recently, score-based diffusion models have shown satisfactory performan...
Many open-domain dialogue models pre-trained with social media comments ...
With the global spread of the COVID-19 pandemic, scientists from various...
Estimated time of arrival (ETA) prediction, also known as travel time
es...
Recently, untrained neural networks (UNNs) have shown satisfactory
perfo...
Generative open-domain dialogue systems can benefit from external knowle...
By learning the map between function spaces using carefully designed dee...
Evolutionary game theory has been a successful tool to combine classical...
We introduce Bi-SimCut: a simple but effective training strategy to boos...
Many recent works indicate that the deep neural networks tend to take da...
While there is increasing concern about the interpretability of neural
m...
Neural retrievers based on pre-trained language models (PLMs), such as
d...
Accurate ADMET (an abbreviation for "absorption, distribution, metabolis...
Emotional support is a crucial skill for many real-world scenarios, incl...
Most dialog systems posit that users have figured out clear and specific...
Parallel imaging is widely used in magnetic resonance imaging as an
acce...
In this paper, we present DuReader_retrieval, a large-scale Chinese data...
Pre-trained models (PTMs) have become a fundamental backbone for downstr...
Vision-Language Pre-training (VLP) has achieved impressive performance o...
Most of the open-domain dialogue models tend to perform poorly in the se...
Recently, a steam of works seek for solving a family of partial differen...
The constrained outbreak of COVID-19 in Mainland China has recently been...
Natural language processing (NLP) task has achieved excellent performanc...
Diagnosis and treatment management for head and neck squamous cell carci...
In this research, an attention-based depthwise separable neural network ...
Conventional methods for the image-text generation tasks mainly tackle t...
Pre-trained language models have achieved state-of-the-art results in va...
Task-oriented dialogue systems have been plagued by the difficulties of
...
Recently, model-driven deep learning unrolls a certain iterative algorit...
In this paper, we focus on studying robustness evaluation of Chinese que...
Distributed training has become a pervasive and effective approach for
t...
Purpose: To propose a novel deep learning-based method called RG-Net
(re...
Machine learning shows great potential in virtual screening for drug
dis...
Most of existing extractive multi-document summarization (MDS) methods s...