  In the NLP community, recent years have seen a surge of research activities
that address machines' ability to perform deep language understanding which
goes beyond what is explicitly stated in text, rather relying on reasoning and
knowledge of the world. Many benchmark tasks and datasets have been created to
support the development and evaluation of such natural language inference
ability. As these benchmarks become instrumental and a driving force for the
NLP research community, this paper aims to provide an overview of recent
benchmarks, relevant knowledge resources, and state-of-the-art learning and
inference approaches in order to support a better understanding of this growing
field.
