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Generating a Common Question from Multiple Documents using Multi source Encoder Decoder Models

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Figure

Figure 1: Multi-Source Question Generator (MSQG)model at test time.The simple architecture signifi-cantly outperforms the baselines for generating com-mon questions, based on a number of metrics.
Table 1: Human evaluation of fluency, relevancy, and answerability. We used the top-ranked 30% of judgesprovided by a crowdsourcing service
Table 3: Full results, comparing models constructedwith M256, M512, and Mattn256 . M512 has the mostnumber of parameters among the three considered.

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