Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Discourse-Aware Neural Rewards for Coherent Text Generation   In this paper, we investigate the use of discourse-aware rewards with
reinforcement learning to guide a model to generate long, coherent text. In
particular, we propose to learn neural rewards to model cross-sentence ordering
as a means to approximate desired discourse structure. Empirical results
demonstrate that a generator trained with the learned reward produces more
coherent and less repetitive text than models trained with cross-entropy or
with reinforcement learning with commonly used scores as rewards.

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The categories of this paper are: cond-mat
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The categories of this paper are: nucl-th
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The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
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The categories of this paper are: math-ph
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The categories of this paper are: nlin
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The categories of this paper are: dg-ga
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The categories of this paper are: adap-org
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The categories of this paper are: q-bio
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The categories of this paper are: hep-th
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The categories of this paper are: quant-ph
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The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
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The categories of this paper are: gr-qc