Narratives are fundamental to our understanding of the world, providing us with a natural
structure for knowledge representation over time. Computational narrative extraction is a …

The task of automatic document summarization aims at generating short summaries for
originally long documents. A good summary should cover the most important information of …

We introduce RealTime QA, a dynamic question answering (QA) platform that announces
questions and evaluates systems on a regular basis (weekly in this version). RealTime QA …

Natural language generation of coherent long texts like paragraphs or longer documents is
a challenging problem for recurrent networks models. In this paper, we explore an important …

With the rapid development and popularization of Internet and mobile communication
technologies, text data mining has attracted much attention. In particular, with the wide use …

Determinantal point processes (DPPs) are elegant probabilistic models of repulsion that
arise in quantum physics and random matrix theory. In contrast to traditional structured …

To establish an automatic conversation system between humans and computers is regarded
as one of the most hardcore problems in computer science, which involves interdisciplinary …

In this paper, we propose the TBCNN-pair model to recognize entailment and contradiction
between two sentences. In our model, a tree-based convolutional neural network (TBCNN) …

We propose an abstraction-based multi-document summarization framework that can
construct new sentences by exploring more fine-grained syntactic units than sentences …

With the explosive growth of microblogging services, short-text messages (also known as
tweets) are being created and shared at an unprecedented rate. Tweets in its raw form can …