Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SPMoE: Generate Multiple Pattern-Aware Outputs with Sparse Pattern
  Mixture of Experts   Many generation tasks follow a one-to-many mapping relationship: each input
could be associated with multiple outputs. Existing methods like Conditional
Variational AutoEncoder(CVAE) employ a latent variable to model this
one-to-many relationship. However, this high-dimensional and dense latent
variable lacks explainability and usually leads to poor and uncontrollable
generations. In this paper, we innovatively introduce the linguistic concept of
pattern to decompose the one-to-many mapping into multiple one-to-one mappings
and further propose a model named Sparse Pattern Mixture of Experts(SPMoE).
Each one-to-one mapping is associated with a conditional generation pattern and
is modeled with an expert in SPMoE. To ensure each language pattern can be
exclusively handled with an expert model for better explainability and
diversity, a sparse mechanism is employed to coordinate all the expert models
in SPMoE. We assess the performance of our SPMoE on the paraphrase generation
task and the experiment results prove that SPMoE can achieve a good balance in
terms of quality, pattern-level diversity, and corpus-level diversity.

13
The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess
7
The categories of this paper are: hep-th