We propose a method based on neural networks to identify the sentiment polarity of opinion
words expressed on a specific aspect of a sentence. Although a large majority of works …

Inductive transfer learning has greatly impacted computer vision, but existing approaches in
NLP still require task-specific modifications and training from scratch. We propose Universal …

Sentiment expression in microblog posts can be affected by user's personal character,
opinion bias, political stance and so on. Most of existing personalized microblog sentiment …

This paper proposes a new model for extracting an interpretable sentence embedding by
introducing self-attention. Instead of using a vector, we use a 2-D matrix to represent the …

Computer vision has benefited from initializing multiple deep layers with weights pretrained
on large supervised training sets like ImageNet. Natural language processing (NLP) …

Semantic role labeling (SRL) is the task of identifying the predicate-argument structure of a
sentence. It is typically regarded as an important step in the standard NLP pipeline. As the …

As the vital technology of natural language understanding, sentence representation
reasoning technology mainly focuses on sentence representation methods and reasoning …

Recurrent Neural Network (RNN) is one of the most popular architectures used in Natural
Language Processsing (NLP) tasks because its recurrent structure is very suitable to …

The current neural network models for event detection have only considered the sequential
representation of sentences. Syntactic representations have not been explored in this area …

Neural network models have been demonstrated to be capable of achieving remarkable
performance in sentence and document modeling. Convolutional neural network (CNN) and …