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Structured Neural Summarization
Tuesday Apr 16 2019 16:00 GMT
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Structured Neural Summarization
Why This Is Interesting

Summarization of long sequences into a concise statement is a core problem in natural language processing, requiring non-trivial understanding of the input. Based on the promising results of graph neural networks on highly structured data, we develop a framework to extend existing sequence encoders with a graph component that can reason about long-distance relationships in weakly structured data such as text. In an extensive evaluation, we show that the resulting hybrid sequence-graph models outperform both pure sequence models as well as pure graph models on a range of summarization tasks.

Time of Recording: Tuesday Apr 16 2019 16:00 GMT