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Found 3 papers, 2 papers with code
Exploring Explainable Selection to Control Abstractive Summarization
A novel pair-wise matrix captures the sentence interactions, centrality, and attribute scores, and a mask with tunable attribute thresholds allows the user to control which sentences are likely to be included in the extraction.
Concept Pointer Network for Abstractive Summarization
A quality abstractive summary should not only copy salient source texts as summaries but should also tend to generate new conceptual words to express concrete details.
Ranked #20 on
Text Summarization
on GigaWord
Adaptive Image Stream Classification via Convolutional Neural Network with Intrinsic Similarity Metrics
Particularly, we utilize a convolution neural network layer that aids in the learning of a latent feature space suitable for novel class detection.
