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

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arxiv 1904.01172 v3 pith:ADXR3QGJ submitted 2019-04-02 cs.CL

classification cs.CL
keywords benchmarksinferencelanguagerecentabilityapproachescommunityknowledge
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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    A new English etiquette corpus and bias metrics show that LLMs over-prefer Western norms and under-predict etiquettes from low-resource regions.

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  3. What Are Research Hypotheses?

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    A position paper documenting inconsistent and often implicit definitions of 'hypothesis' across NLP hypothesis mining tasks and calling for standardization.

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