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Factorizing Content and Budget Decisions in Abstractive Summarization of Long Documents by Sampling Summary Views. (arXiv:2205.12486v1 [cs.CL])
May 26, 2022, 1:12 a.m. | Marcio Fonseca, Yftah Ziser, Shay B. Cohen
cs.CL updates on arXiv.org arxiv.org
We argue that disentangling content selection from the budget used to cover
salient content improves the performance and applicability of abstractive
summarizers. Our method, FactorSum, does this disentanglement by factorizing
summarization into two steps through an energy function: (1) generation of
abstractive summary views; (2) combination of these views into a final summary,
following a budget and content guidance. This guidance may come from different
sources, including from an advisor model such as BART or BigBird, or in oracle
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