Given the overwhelming number of emails, an effective subject line becomes essential to
better inform the recipient of the email's content. In this paper, we propose and study the task …

We present a multi-task learning framework for cross-lingual abstractive summarization to
augment training data. Recent studies constructed pseudo cross-lingual abstractive …

This paper proposes a state-of-the-art recurrent neural network (RNN) language model that
combines probability distributions computed not only from a final RNN layer but also from …

In natural language, the relationship among the constituents of a sentence is usually tree-
like: words, phrases, and clauses constitute a sentence hierarchically, and the dependency …

This paper proposes a novel Recurrent Neural Network (RNN) language model that takes
advantage of character information. We focus on character n-grams based on research in …

There have been many studies on neural headline generation models trained with a lot of
(article, headline) pairs. However, there are few situations for putting such models into …

Ensemble methods, which combine multiple models at decoding time, are now widely
known to be effective for text-generation tasks. However, they generally increase …

User-generated content such as the questions on community question answering (CQA)
forums does not always come with appropriate headlines, in contrast to the news articles …

We propose a novel method for generating titles for unstructured text documents. We
reframe the problem as a sequential question-answering task. A deep neural network is …

We propose the task of video title generation (VTG) and present the YouTube Titles and
Transcripts (YTT) dataset which consists of 17,886 video titles and accompanying …