Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Positioning yourself in the maze of Neural Text Generation: A
  Task-Agnostic Survey   Neural text generation metamorphosed into several critical natural language
applications ranging from text completion to free form narrative generation. In
order to progress research in text generation, it is critical to absorb the
existing research works and position ourselves in this massively growing field.
Specifically, this paper surveys the fundamental components of modeling
approaches relaying task agnostic impacts across various generation tasks such
as storytelling, summarization, translation etc., In this context, we present
an abstraction of the imperative techniques with respect to learning paradigms,
pretraining, modeling approaches, decoding and the key challenges outstanding
in the field in each of them. Thereby, we deliver a one-stop destination for
researchers in the field to facilitate a perspective on where to situate their
work and how it impacts other closely related generation tasks.

33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
0
The categories of this paper are: hep-ph
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
16
The categories of this paper are: stat
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
14
The categories of this paper are: math-ph