Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Generative Approach to Question Answering   Question Answering has come a long way from answer sentence selection,
relational QA to reading and comprehension. We shift our attention to
generative question answering (gQA) by which we facilitate machine to read
passages and answer questions by learning to generate the answers. We frame the
problem as a generative task where the encoder being a network that models the
relationship between question and passage and encoding them to a vector thus
facilitating the decoder to directly form an abstraction of the answer. Not
being able to retain facts and making repetitions are common mistakes that
affect the overall legibility of answers. To counter these issues, we employ
copying mechanism and maintenance of coverage vector in our model respectively.
Our results on MS-MARCO demonstrate it's superiority over baselines and we also
show qualitative examples where we improved in terms of correctness and
readability

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The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
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The categories of this paper are: q-fin
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The categories of this paper are: q-bio
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The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
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The categories of this paper are: bayes-an
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The categories of this paper are: q-alg
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The categories of this paper are: eess
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The categories of this paper are: ao-sci
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The categories of this paper are: gr-qc
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The categories of this paper are: atom-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: dg-ga
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-th