Papers with Multi-perspective Convolutional Cube

1 papers
MCˆ2: Multi-perspective Convolutional Cube for Conversational Machine Reading Comprehension (P19-1)

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Challenge: Existing models combine previous questions for conversation understanding and only employ recurrent neural networks (RNN) for reasoning.
Approach: They propose a multi-perspective convolutional cube model that integrates 1D and 2D convolutions with recurrent neural networks (RNN) to understand context from different perspectives.
Outcome: The proposed model is based on the Conversational Question Answering (CoQA) dataset and achieves state-of-the-art results.

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