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Evaluating Machine Common Sense via Cloze Testing. (arXiv:2201.07902v1 [cs.CL])
Jan. 21, 2022, 2:10 a.m. | Ehsan Qasemi, Lee Kezar, Jay Pujara, Pedro Szekely
cs.CL updates on arXiv.org arxiv.org
Language models (LMs) show state of the art performance for common sense (CS)
question answering, but whether this ability implies a human-level mastery of
CS remains an open question. Understanding the limitations and strengths of LMs
can help researchers improve these models, potentially by developing novel ways
of integrating external CS knowledge. We devise a series of tests and
measurements to systematically quantify their performance on different aspects
of CS. We propose the use of cloze testing combined with word …
More from arxiv.org / cs.CL updates on arXiv.org
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