Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dialogue State Tracking with a Language Model using Schema-Driven
  Prompting   Task-oriented conversational systems often use dialogue state tracking to
represent the user's intentions, which involves filling in values of
pre-defined slots. Many approaches have been proposed, often using
task-specific architectures with special-purpose classifiers. Recently, good
results have been obtained using more general architectures based on pretrained
language models. Here, we introduce a new variation of the language modeling
approach that uses schema-driven prompting to provide task-aware history
encoding that is used for both categorical and non-categorical slots. We
further improve performance by augmenting the prompting with schema
descriptions, a naturally occurring source of in-domain knowledge. Our purely
generative system achieves state-of-the-art performance on MultiWOZ 2.2 and
achieves competitive performance on two other benchmarks: MultiWOZ 2.1 and M2M.
The data and code will be available at
https://github.com/chiahsuan156/DST-as-Prompting.

34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
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The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
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The categories of this paper are: mtrl-th