Attention is an increasingly popular mechanism used in a wide range of neural
architectures. The mechanism itself has been realized in a variety of formats. However …

Recognizing Textual Entailment (RTE) was proposed as a unified evaluation framework to
compare semantic understanding of different NLP systems. In this survey paper, we provide …

Natural language understanding comprises a wide range of diverse tasks such as textual
entailment, question answering, semantic similarity assessment, and document …

Deep learning has improved performance on many natural language processing (NLP)
tasks individually. However, general NLP models cannot emerge within a paradigm that …

When experiencing an information need, users want to engage with a domain expert, but
often turn to an information retrieval system, such as a search engine, instead. Classical …

Many recent state-of-the-art recommender systems such as D-ATT, TransNet and
DeepCoNN exploit reviews for representation learning. This paper proposes a new neural …

Fact verification (FV) is a challenging task which requires to retrieve relevant evidence from
plain text and use the evidence to verify given claims. Many claims require to simultaneously …

Much effort has been devoted to evaluate whether multi-task learning can be leveraged to
learn rich representations that can be used in various Natural Language Processing (NLP) …

In this paper, we present a fast and strong neural approach for general purpose text
matching applications. We explore what is sufficient to build a fast and well-performed text …

Sentence matching is widely used in various natural language tasks such as natural
language inference, paraphrase identification, and question answering. For these tasks …