This paper proposes a grant-free massive access scheme based on the
mill...
The existing supervised relation extraction methods have achieved impres...
More and more edge devices and mobile apps are leveraging deep learning ...
Pretrained language models have achieved remarkable success in various
n...
Automated program repair is an emerging technology which consists of a s...
Image cartoonization is recently dominated by generative adversarial net...
We propose an end-to-end-trainable feature augmentation module built for...
Large language models, e.g., Codex and AlphaCode, have shown capability ...
Due to the wavelength-dependent light attenuation, refraction and scatte...
Automated program repair is an emerging technology that seeks to
automat...
Objective: We develop a computer-aided diagnosis (CAD) system using deep...
Recent advances in large-scale pre-training such as GPT-3 allow seemingl...
The design of better automated dialogue evaluation metrics offers the
po...
Existing open-domain dialog models are generally trained to minimize the...
This study is motivated by a new class of challenging control problems
d...
We present MixingBoard, a platform for quickly building demos with a foc...
Current end-to-end neural conversation models inherently lack the flexib...
When trained effectively, the Variational Autoencoder (VAE) can be both ...
The prevalence of accessible depth sensing and 3D laser scanning techniq...
Recent advances in Graph Convolutional Neural Networks (GCNNs) have show...
We present a large, tunable neural conversational response generation mo...
Graph Convolutional Neural Networks (GCNNs) extend classical CNNs to gra...
Generating responses in a targeted style is a useful yet challenging tas...
Identifying an appropriate underlying graph kernel that reflects pairwis...
Although neural conversation models are effective in learning how to pro...
The prevalence of accessible depth sensing and 3D laser scanning techniq...
Semi-supervised classification on graph-structured data has received
inc...
Image based modeling and laser scanning are two commonly used approaches...
Recently, data-driven based Automatic Speech Recognition (ASR) systems h...
Accurate and robust visual localization under a wide range of viewing
co...
Generating responses that are consistent with the dialogue context is on...
The computer-aided detection (CADe) systems are developed to assist
path...
Although recent neural conversation models have shown great potential, t...
This paper introduces the Seventh Dialog System Technology Challenges (D...
With the prevalence of accessible depth sensors, dynamic human body skel...
In this paper we present an extension of Direct Sparse Odometry (DSO) to...
In this paper, we propose a novel Global Norm-Aware Pooling (GNAP) block...
In this paper, we present a class of extremely efficient CNN models call...
Structure-from-Motion approaches could be broadly divided into two class...
Deep Q-learning is investigated as an end-to-end solution to estimate th...
Recent years have witnessed the rapid development and wide adoption of
i...
Monocular visual odometry (VO) has seen tremendous improvements in accur...
In this paper we propose a randomized primal-dual proximal block coordin...