Harnessing the Power of Text-image Contrastive Models for Automatic Detection of Online Misinformation
Author:
Affiliation:
1. Chengdu University of Information Technology
2. University at Buffalo,USA
3. Carnegie Mellon University,USA
4. Microsoft,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10208270/10208119/10208950.pdf?arnumber=10208950
Reference47 articles.
1. NileTMRG at SemEval-2017 Task 8: Determining Rumour and Veracity Support for Rumours on Twitter.
2. The Surprising Performance of Simple Baselines for Misinformation Detection
3. An image is worth 16x16 words: Transformers for image recognition at scale;dosovitskiy,2020
4. Representation learning with contrastive predictive coding;den oord,2018
5. SimCSE: Simple Contrastive Learning of Sentence Embeddings
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1. Few-Shot Learning for Misinformation Detection Based on Contrastive Models;Electronics;2024-02-19
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