  Identifying the difference between two versions of the same article is useful
to update knowledge bases and to understand how articles evolve. Paired texts
occur naturally in diverse situations: reporters write similar news stories and
maintainers of authoritative websites must keep their information up to date.
We propose representing factual changes between paired documents as
question-answer pairs, where the answer to the same question differs between
two versions. We find that question-answer pairs can flexibly and concisely
capture the updated contents. Provided with paired documents, annotators
identify questions that are answered by one passage but answered differently or
cannot be answered by the other. We release DIFFQG which consists of 759 QA
pairs and 1153 examples of paired passages with no factual change. These
questions are intended to be both unambiguous and information-seeking and
involve complex edits, pushing beyond the capabilities of current question
generation and factual change detection systems. Our dataset summarizes the
changes between two versions of the document as questions and answers, studying
automatic update summarization in a novel way.
