To address the summarization alignment, former studies try to apply an attention mechanism to measure the saliency/novelty of each candidate word/sentence (Tan et al., 2017), with the aim of locating the most representative content to retain primary coverage.
to our best knowledge, we make the first attempt to develop a neural data-driven solution for the automatic related work summarization, and the practice of using the joint context as an attention cue is also less explored to date.