Multimodal News Article Analysis
By Arnau Ramisa. 2017
9 citations recorded by the source corpus.
The intersection of Computer Vision and Natural Language Processing has been a hot topic of research in recent years, with results that were unthinkable only a few years ago. In view of this progress, we want to highlight online news articles as a potential next step for this area of research. The rich interrelations of text, tags, images or videos, as well as a vast corpus of general knowledge are an exciting benchmark for high-capacity models such as the deep neural networks. In this paper we present a series of tasks and baseline approaches to leverage corpus such as the BreakingNews dataset.
Subfields: Natural Language Processing, Multimodal Learning
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Natural Language Processing
- Douwe Kiela
- Amanpreet Singh
- Pratik Ringshia
- Vedanuj Goswami
- Davide Testuggine
- Aravind Mohan
- Hamed Firooz
- Samuel R. Bowman
In Multimodal Learning
- Davide Testuggine
- Pratik Ringshia
- Douwe Kiela
- Aravind Mohan
- Hamed Firooz
- Vedanuj Goswami
- Amanpreet Singh
- Ronghang Hu
Citations in the corpus
- The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes (2020, methodology): “Other datasets using internet data include Food101 [80], where the goal is to predict the dish of recipes and images; various versions of Yelp reviews [52]; Walmart and Ferramenta product classification [90, 21]; social media name tagging (Twitter and Snapchat) [49]; social media target-oriented sen”