Sandeep Polisetty


2021

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InfoSurgeon: Cross-Media Fine-grained Information Consistency Checking for Fake News Detection
Yi Fung | Christopher Thomas | Revanth Gangi Reddy | Sandeep Polisetty | Heng Ji | Shih-Fu Chang | Kathleen McKeown | Mohit Bansal | Avi Sil
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

To defend against machine-generated fake news, an effective mechanism is urgently needed. We contribute a novel benchmark for fake news detection at the knowledge element level, as well as a solution for this task which incorporates cross-media consistency checking to detect the fine-grained knowledge elements making news articles misinformative. Due to training data scarcity, we also formulate a novel data synthesis method by manipulating knowledge elements within the knowledge graph to generate noisy training data with specific, hard to detect, known inconsistencies. Our detection approach outperforms the state-of-the-art (up to 16.8% accuracy gain), and more critically, yields fine-grained explanations.