Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Improving Multi-turn Dialogue Modelling with Utterance ReWriter   Recent research has made impressive progress in single-turn dialogue
modelling. In the multi-turn setting, however, current models are still far
from satisfactory. One major challenge is the frequently occurred coreference
and information omission in our daily conversation, making it hard for machines
to understand the real intention. In this paper, we propose rewriting the human
utterance as a pre-process to help multi-turn dialgoue modelling. Each
utterance is first rewritten to recover all coreferred and omitted information.
The next processing steps are then performed based on the rewritten utterance.
To properly train the utterance rewriter, we collect a new dataset with human
annotations and introduce a Transformer-based utterance rewriting architecture
using the pointer network. We show the proposed architecture achieves
remarkably good performance on the utterance rewriting task. The trained
utterance rewriter can be easily integrated into online chatbots and brings
general improvement over different domains.

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The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex