Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dialogue Learning With Human-In-The-Loop   An important aspect of developing conversational agents is to give a bot the
ability to improve through communicating with humans and to learn from the
mistakes that it makes. Most research has focused on learning from fixed
training sets of labeled data rather than interacting with a dialogue partner
in an online fashion. In this paper we explore this direction in a
reinforcement learning setting where the bot improves its question-answering
ability from feedback a teacher gives following its generated responses. We
build a simulator that tests various aspects of such learning in a synthetic
environment, and introduce models that work in this regime. Finally, real
experiments with Mechanical Turk validate the approach.

17
The categories of this paper are: q-fin
15
The categories of this paper are: nucl-ex
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
19
The categories of this paper are: eess
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
30
The categories of this paper are: q-alg
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph