Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Incremental Transformer with Deliberation Decoder for Document Grounded
  Conversations   Document Grounded Conversations is a task to generate dialogue responses when
chatting about the content of a given document. Obviously, document knowledge
plays a critical role in Document Grounded Conversations, while existing
dialogue models do not exploit this kind of knowledge effectively enough. In
this paper, we propose a novel Transformer-based architecture for multi-turn
document grounded conversations. In particular, we devise an Incremental
Transformer to encode multi-turn utterances along with knowledge in related
documents. Motivated by the human cognitive process, we design a two-pass
decoder (Deliberation Decoder) to improve context coherence and knowledge
correctness. Our empirical study on a real-world Document Grounded Dataset
proves that responses generated by our model significantly outperform
competitive baselines on both context coherence and knowledge relevance.

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The categories of this paper are: gr-qc
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The categories of this paper are: cond-mat
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The categories of this paper are: nlin
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The categories of this paper are: eess
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The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
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The categories of this paper are: hep-lat
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The categories of this paper are: quant-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-ex
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The categories of this paper are: physics
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The categories of this paper are: hep-ex
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The categories of this paper are: stat
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The categories of this paper are: comp-gas
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The categories of this paper are: nucl-th