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cs.MM2026
ReVR: Dual-Path Concept Reasoning for Multimodal Fake News Detection
Zhikai Tan, Yuzhou Yang, Qichao Ying +4
Vision-language models (VLMs) support multimodal fake news detection (FND) by producing explicit analyses. Recent methods further improve interpretability by organizing verificatio…
cs.MM2026
Self-Reflective Multi-modal Reasoning for Short-Video Fake News Detection
Pinjie Xu, Yuzhou Yang, Zhikai Tan +4
Recent fake news detection pipelines increasingly leverage large language models and vision-language models for reasoning-based analysis. However, several challenges remain open: i…
cs.MM2026
RoE-FND: Synergizing LLMs with Experiential Learning for Effective and Generalizable Evidence-Based Fake News Detection
Yuzhou Yang, Qichao Ying, Sheng Li +3
The proliferation of deceptive content in social networks necessitates robust Fake News Detection (FND) systems. Existing pipelines either train detectors on labeled data or levera…