Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: What Went Wrong? Explaining Overall Dialogue Quality through
  Utterance-Level Impacts   Improving user experience of a dialogue system often requires intensive
developer effort to read conversation logs, run statistical analyses, and
intuit the relative importance of system shortcomings. This paper presents a
novel approach to automated analysis of conversation logs that learns the
relationship between user-system interactions and overall dialogue quality.
Unlike prior work on utterance-level quality prediction, our approach learns
the impact of each interaction from the overall user rating without
utterance-level annotation, allowing resultant model conclusions to be derived
on the basis of empirical evidence and at low cost. Our model identifies
interactions that have a strong correlation with the overall dialogue quality
in a chatbot setting. Experiments show that the automated analysis from our
model agrees with expert judgments, making this work the first to show that
such weakly-supervised learning of utterance-level quality prediction is highly
achievable.

30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
23
The categories of this paper are: solv-int
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
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The categories of this paper are: cmp-lg
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The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio
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The categories of this paper are: bayes-an