Papers with gated self-attention encoder

1 papers
Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks (D18-1)

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Challenge: Existing rule-based question generation models rely on one or two sentences as input, while long text has posed challenges for sequence to sequence neural models.
Approach: They propose a maxout pointer mechanism with gated self-attention encoder to address the challenges of processing long text inputs for question generation.
Outcome: The proposed model outperforms existing models with sentence-level or paragraph-level inputs pushing the state-of-the-art result from 13.9 to 16.3 (BLEU_4).

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