Aspect-based sentiment analysis aims to determine the sentiment polarity towards a specific
aspect in online reviews. Most recent efforts adopt attention-based neural network models to …

We present simple BERT-based models for relation extraction and semantic role labeling. In
recent years, state-of-the-art performance has been achieved using neural models by …

Dependency trees help relation extraction models capture long-range relations between
words. However, existing dependency-based models either neglect crucial information (eg …

Aspect-based sentiment analysis aims to analyze the sentiment polarity of a given aspect.
The graph convolutional neural network model is widely used. However, most existing …

Multi-turn conversation understanding is a major challenge for building intelligent dialogue
systems. This work focuses on retrieval-based response matching for multi-turn conversation …

It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the
use of the glyph information in those languages. However, due to the lack of rich …

Abstract Aspect-based Sentiment Analysis (ABSA) is a subclass of sentiment analysis, which
aims to identify the sentiment polarity such as positive, negative, or neutral for specific …

Hierarchical text classification is an essential yet challenging subtask of multi-label text
classification with a taxonomic hierarchy. Existing methods have difficulties in modeling the …

Named entity recognition (NER) models are typically based on the architecture of Bi-
directional LSTM (BiLSTM). The constraints of sequential nature and the modeling of single …

Head-driven phrase structure grammar (HPSG) enjoys a uniform formalism representing rich
contextual syntactic and even semantic meanings. This paper makes the first attempt to …