Papers with multi-source encoder-decoder framework

1 papers
Generating a Common Question from Multiple Documents using Multi-source Encoder-Decoder Models (D19-56)

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Challenge: Ambiguous user queries can result in multiple topics being retrieved from search engines.
Approach: They propose a task of generating a common question from multiple documents by training an RNN-based single encoder-decoder generator from document pairs and then a model that aggregates these word distributions to generate a question.
Outcome: The proposed model significantly outperforms existing models when evaluated using automated metrics and human judgments on the MS-MARCO-QA dataset.

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