News Validator: A Multimodal, Confidence-Aware Framework for Real-Time Fake News Detection Using OCR, NLP, and Large Language Models

In this paper a multimodal fake news detection system is proposed combining the use of OCR, NLP and LLMs to help identify false and misleading information. The proposed system can be trained on multi-modal inputs and I believe it will work well on current social media data, which is mostly multimodal. The use of OCR allows for extraction of the actual text from images of memes, screen shots and text present within the post. The extracted text will then be processed using NLP techniques so as to analyze the linguistics, semantics, and context of the text. The utilization of state of the art LLMs will further improve the classification accuracy and reliability. The real time predictions along with a confidence score is an another interesting feature of the proposed system. The confidence score predicts the reliability of the prediction which can be utilized for decision making. This makes the system a perfect candidate for use in real life scenarios such as blogging, automated chat monitoring. Although it shows promising results, a couple of issues and directions for future research need to be addressed. First, the incorporation of multi-lingual data can help the system to be adaptable to different languages, expanding its global usability. Second, using video frames analysis and audio-text processing can open new doors for the system in the detecting misinformation among multime-dia content. In addition, or alternatively, the bringing in of-factcheckingAPIs could enhance credibility of the system if it were able to cross-verify facts in the system database in real time against trusted sources. Then the system could classify also on grounds of evidence. To sum up, the advanced multimodal architecture sug-gested by the article provides an effectual and scalable framework for combating fake news and preventing the proliferation of the issue. Improvements for the frame-work such as support for multilingual processing, video analysis, and verification of news items in real-time are are anticipated to be beneficial.

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