Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Clue: Cross-modal Coherence Modeling for Caption Generation   We use coherence relations inspired by computational models of discourse to
study the information needs and goals of image captioning. Using an annotation
protocol specifically devised for capturing image--caption coherence relations,
we annotate 10,000 instances from publicly-available image--caption pairs. We
introduce a new task for learning inferences in imagery and text, coherence
relation prediction, and show that these coherence annotations can be exploited
to learn relation classifiers as an intermediary step, and also train
coherence-aware, controllable image captioning models. The results show a
dramatic improvement in the consistency and quality of the generated captions
with respect to information needs specified via coherence relations.

24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
37
The categories of this paper are: supr-con
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an