Original: Inspired by Google's Neural Machine Translation (NMT) \mbox{%DIFAUXCMD Wu2016Google that models the one-to-one alignment in translation tasks with an optimal uniform attention distribution during the inference, this study proposes an attention-aware inference algorithm for Neural Abstractive Summarization (NAS) to regulate generated summaries to attend to source paragraphs/sentences with the optimal coverage.
Revised: Inspired by Google's Neural Machine Translation (NMT) \mbox{%DIFAUXCMD Wu2016Google that models the one-to-one alignment in translation tasks with an optimal uniform attention distribution during the inference, this study proposes an attention-aware inference algorithm for Neural Abstractive Summarization (NAS) to regulate generated summaries to attend to source contents with the optimal coverage.
Edit intent: meaning-changed