Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Why are Sequence-to-Sequence Models So Dull? Understanding the
  Low-Diversity Problem of Chatbots   Diversity is a long-studied topic in information retrieval that usually
refers to the requirement that retrieved results should be non-repetitive and
cover different aspects. In a conversational setting, an additional dimension
of diversity matters: an engaging response generation system should be able to
output responses that are diverse and interesting. Sequence-to-sequence
(Seq2Seq) models have been shown to be very effective for response generation.
However, dialogue responses generated by Seq2Seq models tend to have low
diversity. In this paper, we review known sources and existing approaches to
this low-diversity problem. We also identify a source of low diversity that has
been little studied so far, namely model over-confidence. We sketch several
directions for tackling model over-confidence and, hence, the low-diversity
problem, including confidence penalties and label smoothing.

21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
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The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
27
The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th
32
The categories of this paper are: atom-ph
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat