Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Quality Assurance of Generative Dialog Models in an Evolving
  Conversational Agent Used for Swedish Language Practice   Due to the migration megatrend, efficient and effective second-language
acquisition is vital. One proposed solution involves AI-enabled conversational
agents for person-centered interactive language practice. We present results
from ongoing action research targeting quality assurance of proprietary
generative dialog models trained for virtual job interviews. The action team
elicited a set of 38 requirements for which we designed corresponding automated
test cases for 15 of particular interest to the evolving solution. Our results
show that six of the test case designs can detect meaningful differences
between candidate models. While quality assurance of natural language
processing applications is complex, we provide initial steps toward an
automated framework for machine learning model selection in the context of an
evolving conversational agent. Future work will focus on model selection in an
MLOps setting.

17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
2
The categories of this paper are: math
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc