Improving Conditioning in Context-Aware Sequence to Sequence Models

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Abstract:

Neural sequence to sequence models are well established for applications which can be cast as mapping a single input sequence into a single output sequence. In this work, we focus on cases where generation is conditioned on both a short query and a long context, such as abstractive question answering or document-level translation. We mo...More

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