arXiv:2206.13981
공식 코드 · Papers with Code
Hybrid Ensemble for Fake News Detection: An attempt
원문 초록
Fake News Detection has been a challenging problem in the field of Machine Learning. Researchers have approached it via several techniques using old Statistical Classification models and modern Deep Learning. Today, with the growing amount of data, developments in the field of NLP and ML, and an increase in the computation power at disposal, there are infinite permutations and combinations to approach this problem from a different perspective. In this paper, we try different methods to tackle Fake News, and try to build, and propose the possibilities of a Hybrid Ensemble combining the classical Machine Learning techniques with the modern Deep Learning Approaches
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Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection
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Multimodal Fake News Detection: MFND Dataset and Shallow-Deep Multitask Learning
A Python Tool for Reconstructing Full News Text from GDELT
Multi-view autoencoders for Fake News Detection
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