ArT: All-round Thinker for Unsupervised Commonsense Question-Answering. (arXiv:2112.13428v2 [cs.CL] UPDATED)

Without labeled question-answer pairs for necessary training, unsupervised
commonsense question-answering (QA) appears to be extremely challenging due to
its indispensable unique prerequisite on commonsense source like knowledge
bases (KBs), which are usually highly resource consuming in construction.
Recently pre-trained language models (PLMs) show effectiveness as an
alternative for commonsense clues when they play a role of knowledge generator.
However, existing work either relies on large-scale in-domain or out-of-domain
labeled data, or fails to generate knowledge of high quality in a …

art arxiv unsupervised