CLApr 2, 2019

Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches

arXiv:1904.01172v3144 citations
Originality Synthesis-oriented
AI Analysis

It synthesizes existing work to support the NLP community in understanding and advancing natural language inference, but is incremental as it does not introduce new methods or results.

This survey paper provides an overview of recent benchmarks, resources, and state-of-the-art approaches in natural language inference, addressing machines' ability to perform deep language understanding beyond explicit text.

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.

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Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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