Designing a strong test for measuring true common-sense reasoning

Kejriwal, Mayank; Santos, Henrique; Mulvehill, Alice; McGuinness, Deborah L.

Author

Kejriwal, Mayank; Santos, Henrique; Mulvehill, Alice; McGuinness, Deborah L.

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Date Issued

2022-04-22

Subject

Common-sense reasoning; artificial intelligence

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Full Citation

Kejriwal, M., Santos, H., Mulvehill, A.M. et al. Designing a strong test for measuring true common-sense reasoning. Nat Mach Intell 4, 318–322 (2022).

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URI

https://rdcu.be/cLUHR; https://hdl.handle.net/20.500.13015/4979

Abstract

Common-sense reasoning has recently emerged as an important test for artificial general intelligence, especially given the much-publicized successes of language representation models such as T5, BERT and GPT-3. Currently, typical benchmarks involve question answering tasks, but to test the full complexity of common-sense reasoning, more comprehensive evaluation methods that are grounded in theory should be developed.;