Abstract:Summarization datasets are often assembled either by scraping naturally occurring publicdomain summaries-which are nearly always in difficult-to-work-with technical domainsor by using approximate heuristics to extract them from everyday text-which frequently yields unfaithful summaries. In this work, we turn to a slower but more straightforward approach to developing summarization benchmark data: We hire highly-qualified contractors to read stories and write original summaries from scratch. To amortize reading… Show more
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