AI Bibliography
AI Bibliography |
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Kocijan, V., Lukasiewicz, T., Davis, E., Marcus, G., & Morgenstern, L. (2020). A review of winograd schema challenge datasets and approaches. arXiv preprint arXiv:2004.13831. |
| Resource type: Journal Article BibTeX citation key: Kocijan2020 View all bibliographic details  |
Categories: Artificial Intelligence, Cognitive Science, Complexity Science, Computer Science, Data Sciences, Decision Theory, General, Mathematics Subcategories: Analytics, Big data, Decision making, Deep learning, Human decisionmaking, Human learning, Machine learning, Machine recognition, Neural nets, Neurosymbolic Creators: Davis, Kocijan, Lukasiewicz, Marcus, Morgenstern Publisher: Collection: arXiv preprint arXiv:2004.13831 |
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| Abstract |
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The Winograd Schema Challenge is both a commonsense reasoning and natural language understanding challenge, introduced as an alternative to the Turing test. A Winograd schema is a pair of sentences differing in one or two words with a highly ambiguous pronoun, resolved differently in the two sentences, that appears to require commonsense knowledge to be resolved correctly. The examples were designed to be easily solvable by humans but difficult for machines, in principle requiring a deep understanding of the content of the text and the situation it describes. This paper reviews existing Winograd Schema Challenge benchmark datasets and approaches that have been published since its introduction.
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