QuAC (Question Answering in Context)

Introduced by Choi et al. in QuAC: Question Answering in Context

Question Answering in Context is a large-scale dataset that consists of around 14K crowdsourced Question Answering dialogs with 98K question-answer pairs in total. Data instances consist of an interactive dialog between two crowd workers: (1) a student who poses a sequence of freeform questions to learn as much as possible about a hidden Wikipedia text, and (2) a teacher who answers the questions by providing short excerpts (spans) from the text.

Source: https://paperswithcode.com/paper/quac-question-answering-in-context-1/


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