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

Abstract

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.

References in corpus (28)

• Efficient Estimation of Word Representations in Vector Space
• Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
• XLNet: Generalized Autoregressive Pretraining for Language Understanding
• Enhanced LSTM for Natural Language Inference
• VQA: Visual Question Answering
• ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
• ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
• End-To-End Memory Networks
• The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations
• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• Neural Natural Language Inference Models Enhanced with External Knowledge
• Visual Question Answering: Datasets, Algorithms, and Future Challenges
• Multi-Task Deep Neural Networks for Natural Language Understanding
• ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension
• Tracking the World State with Recurrent Entity Networks
• Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
• The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants
• WinoGrande: An Adversarial Winograd Schema Challenge at Scale
• Query-Reduction Networks for Question Answering
• Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
• How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG
• Abductive Commonsense Reasoning
• A Survey on Semantic Parsing
• Tracking State Changes in Procedural Text: A Challenge Dataset and Models for Process Paragraph Comprehension
• HFL-RC System at SemEval-2018 Task 11: Hybrid Multi-Aspects Model for Commonsense Reading Comprehension
• Reasoning about Actions and State Changes by Injecting Commonsense Knowledge
• ASER: A Large-scale Eventuality Knowledge Graph
• Machine Common Sense

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• Consolidating Commonsense Knowledge
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• Natural Language QA Approaches using Reasoning with External Knowledge
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• Towards Tractable Mathematical Reasoning: Challenges, Strategies, and Opportunities for Solving Math Word Problems
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