Commonsense knowledge is vital to many natural language processing tasks. In this paper,
we present a novel open-domain conversation generation model to demonstrate how large …

Although the Transformer translation model (Vaswani et al., 2017) has achieved state-of-the-
art performance in a variety of translation tasks, how to use document-level context to deal …

This paper concerns a deep learning approach to relevance ranking in information retrieval
(IR). Existing deep IR models such as DSSM and CDSSM directly apply neural networks to …

Endowing a chatbot with personality or an identity is quite challenging but critical to deliver
more realistic and natural conversations. In this paper, we address the issue of generating …

A high efficient production of fatty acid methyl ester (FAME) from soybean oil and rapeseed
oil was carried out using modified CaO as solid basic catalyst by connecting bromooctane to …

Congenital heart diseases (CHD) are the most common birth defects, and the early
diagnosis of CHD is crucial for CHD therapy. However, there are relatively few studies on …

Due to the benefits of model compactness, multilingual translation (including many-to-one,
many-to-many and one-to-many) based on a universal encoder-decoder architecture …

Although neural machine translation has made significant progress recently, how to
integrate multiple overlapping, arbitrary prior knowledge sources remains a challenge. In …

Graphs are an important abstraction used in many scientific fields. With the magnitude of
graph-structured data constantly increasing, effective data analytics requires efficient and …

Multilingual neural machine translation (Multi-NMT) with one encoder-decoder model has
made remarkable progress due to its simple deployment. However, this multilingual …