Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Multi-Modal Method for Satire Detection using Textual and Visual Cues   Satire is a form of humorous critique, but it is sometimes misinterpreted by
readers as legitimate news, which can lead to harmful consequences. We observe
that the images used in satirical news articles often contain absurd or
ridiculous content and that image manipulation is used to create fictional
scenarios. While previous work have studied text-based methods, in this work we
propose a multi-modal approach based on state-of-the-art visiolinguistic model
ViLBERT. To this end, we create a new dataset consisting of images and
headlines of regular and satirical news for the task of satire detection. We
fine-tune ViLBERT on the dataset and train a convolutional neural network that
uses an image forensics technique. Evaluation on the dataset shows that our
proposed multi-modal approach outperforms image-only, text-only, and simple
fusion baselines.

25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
20
The categories of this paper are: acc-phys
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
5
The categories of this paper are: gr-qc
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph