Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Masked Non-Autoregressive Image Captioning   Existing captioning models often adopt the encoder-decoder architecture,
where the decoder uses autoregressive decoding to generate captions, such that
each token is generated sequentially given the preceding generated tokens.
However, autoregressive decoding results in issues such as sequential error
accumulation, slow generation, improper semantics and lack of diversity.
Non-autoregressive decoding has been proposed to tackle slow generation for
neural machine translation but suffers from multimodality problem due to the
indirect modeling of the target distribution. In this paper, we propose masked
non-autoregressive decoding to tackle the issues of both autoregressive
decoding and non-autoregressive decoding. In masked non-autoregressive
decoding, we mask several kinds of ratios of the input sequences during
training, and generate captions parallelly in several stages from a totally
masked sequence to a totally non-masked sequence in a compositional manner
during inference. Experimentally our proposed model can preserve semantic
content more effectively and can generate more diverse captions.

19
The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat