Realistic Data Augmentation Framework for Enhancing Tabular Reasoning Article Swipe
Dibyakanti Kumar
,
Vivek Gupta
,
Soumya Sharma
,
Shuo Zhang
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2210.12795
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2210.12795
Existing approaches to constructing training data for Natural Language Inference (NLI) tasks, such as for semi-structured table reasoning, are either via crowdsourcing or fully automatic methods. However, the former is expensive and time-consuming and thus limits scale, and the latter often produces naive examples that may lack complex reasoning. This paper develops a realistic semi-automated framework for data augmentation for tabular inference. Instead of manually generating a hypothesis for each table, our methodology generates hypothesis templates transferable to similar tables. In addition, our framework entails the creation of rational counterfactual tables based on human written logical constraints and premise paraphrasing. For our case study, we use the InfoTabs, which is an entity-centric tabular inference dataset. We observed that our framework could generate human-like tabular inference examples, which could benefit training data augmentation, especially in the scenario with limited supervision.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2210.12795
- https://arxiv.org/pdf/2210.12795
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4307313316
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4307313316Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2210.12795Digital Object Identifier
- Title
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Realistic Data Augmentation Framework for Enhancing Tabular ReasoningWork title
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-10-23Full publication date if available
- Authors
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Dibyakanti Kumar, Vivek Gupta, Soumya Sharma, Shuo ZhangList of authors in order
- Landing page
-
https://arxiv.org/abs/2210.12795Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2210.12795Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2210.12795Direct OA link when available
- Concepts
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Inference, Computer science, Counterfactual thinking, Premise, Table (database), Crowdsourcing, Artificial intelligence, Machine learning, Natural language processing, Data mining, Epistemology, Linguistics, World Wide Web, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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