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- W2325162016 abstract "Examples of the present disclosure provide systems and methods relating to a machine comprehension test with a learning-based approach, harnessing neural networks arranged in a parallel hierarchy. This parallel hierarchy enables the model to compare the passage, question, and answer from a variety of perspectives, as opposed to using a manually designed set of features. Perspectives may range from the word level to sentence fragments to sequences of sentences, and networks operate on word-embedding representations of text. A training methodology for small data is also provided." @default.
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- W2325162016 date "2016-01-01" @default.
- W2325162016 modified "2023-10-16" @default.
- W2325162016 title "A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data" @default.
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- W2325162016 doi "https://doi.org/10.18653/v1/p16-1041" @default.
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