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Found 4 papers, 0 papers with code
Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network
Sentence-level extractive text summarization is substantially a node classification task of network mining, adhering to the informative components and concise representations.
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Extractive Text Summarization
on CNN / Daily Mail
TEBNER: Domain Specific Named Entity Recognition with Type Expanded Boundary-aware Network
To alleviate label scarcity in Named Entity Recognition (NER) task, distantly supervised NER methods are widely applied to automatically label data and identify entities.
Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization
In zero-shot multilingual extractive text summarization, a model is typically trained on English summarization dataset and then applied on summarization datasets of other languages.
Deep Differential Amplifier for Extractive Summarization
In this paper, we conceptualize the single-document extractive summarization as a rebalance problem and present a deep differential amplifier framework.
