Papers by Reuben Tan
Detecting Cross-Modal Inconsistency to Defend Against Neural Fake News (2020.emnlp-main)
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| Challenge: | Existing approaches to defend against fake news are limited to text and metadata . authors identify weaknesses that adversaries can exploit by manipulating such technology . |
| Approach: | They propose a more realistic defense mechanism to defend against machine-generated news . they use a NeuralNews dataset to identify weaknesses that adversaries can exploit . |
| Outcome: | The proposed approach detects visual-semantic inconsistencies and provides a useful first line of defense against machine-generated disinformation. |