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FakeNewsGPT4: Advancing Multimodal Fake News Detection through Knowledge-Augmented LVLMs
March 5, 2024, 2:52 p.m. | Xuannan Liu, Peipei Li, Huaibo Huang, Zekun Li, Xing Cui, Jiahao Liang, Lixiong Qin, Weihong Deng, Zhaofeng He
cs.CL updates on arXiv.org arxiv.org
Abstract: The massive generation of multimodal fake news exhibits substantial distribution discrepancies, prompting the need for generalized detectors. However, the insulated nature of training within specific domains restricts the capability of classical detectors to obtain open-world facts. In this paper, we propose FakeNewsGPT4, a novel framework that augments Large Vision-Language Models (LVLMs) with forgery-specific knowledge for manipulation reasoning while inheriting extensive world knowledge as complementary. Knowledge augmentation in FakeNewsGPT4 involves acquiring two types of forgery-specific knowledge, …
abstract arxiv capability cs.cl detection distribution domains facts fake fake news framework generalized knowledge massive multimodal nature novel open-world paper prompting through training type world
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