Many business workflows require extracting important fields from form-li...
A key bottleneck in building automatic extraction models for visually ri...
COVID-19 has caused lasting damage to almost every domain in public heal...
The clinical named entity recognition (CNER) task seeks to locate and
cl...
The optimization problems associated with training generative adversaria...
Clinical case reports are written descriptions of the unique aspects of ...
There has been a steady need to precisely extract structured knowledge f...
There has been a steady need in the medical community to precisely extra...
Extracting event temporal relations is a critical task for information
e...
In the online advertising industry, the process of designing an ad creat...
We present HoliCity, a city-scale 3D dataset with rich structural
inform...
3D reconstruction from a single RGB image is a challenging problem in
co...
We present ManifoldPlus, a method for robust and scalable conversion of
...
Humor plays an important role in human languages and it is essential to ...
There is a perennial need in the online advertising industry to refresh ...
We present a simple yet effective end-to-end trainable deep network with...
Adversarial attacks against machine learning models have threatened vari...
In this paper, we propose a method to obtain a compact and accurate 3D
w...
We present a conceptually simple yet effective algorithm to detect wiref...
In this work, we introduce the novel problem of identifying dense canoni...
In this paper, we propose a recurrent neural network (RNN)-based MIDI mu...
Word embedding models have become a fundamental component in a wide rang...
Precision medicine and health requires the characterization and phenotyp...
The computation of the global minimum energy conformation (GMEC) is an
i...