Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog
  System   We present MEDCOD, a Medically-Accurate, Emotive, Diverse, and Controllable
Dialog system with a unique approach to the natural language generator module.
MEDCOD has been developed and evaluated specifically for the history taking
task. It integrates the advantage of a traditional modular approach to
incorporate (medical) domain knowledge with modern deep learning techniques to
generate flexible, human-like natural language expressions. Two key aspects of
MEDCOD's natural language output are described in detail. First, the generated
sentences are emotive and empathetic, similar to how a doctor would communicate
to the patient. Second, the generated sentence structures and phrasings are
varied and diverse while maintaining medical consistency with the desired
medical concept (provided by the dialogue manager module of MEDCOD).
Experimental results demonstrate the effectiveness of our approach in creating
a human-like medical dialogue system. Relevant code is available at
https://github.com/curai/curai-research/tree/main/MEDCOD

8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
35
The categories of this paper are: mtrl-th
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
34
The categories of this paper are: chem-ph
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph