We study the problem of generating counterfactual text for a classifier ...
Recently, there has been a significant interest in performing convolutio...
Recent neural models for relation extraction with distant supervision
al...
We present a new local entity disambiguation system. The key to our syst...
Deep learning has emerged as a compelling solution to many NLP tasks wit...
Recognizing sarcasm often requires a deep understanding of multiple sour...
Deep learning models have achieved remarkable success in natural languag...
In this paper, we present a novel model for entity disambiguation that
c...
We present a novel deep learning architecture to address the cloze-style...
Traditional event detection methods heavily rely on manually engineered ...
We present a novel deep learning architecture to address the natural lan...
We present a probabilistic modeling and inference framework for
discrimi...
Multi-instance data, in which each object (bag) contains a collection of...
Labeling data for classification requires significant human effort. To r...
Bird sound data collected with unattended microphones for automatic surv...