From Form to Logic: Masked Reconstruction and Reasoning Distillation for Short Video Fake News Detection (2026.acl-long)
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| Challenge: | Existing detectors that detect short video fake news suffer from global-alignment bias and lack generative reasoning are too late. |
| Approach: | They propose a Perception-Cognition Dual-driven Detector that jointly observes the form and probes the logic for short video fake news detection. |
| Outcome: | The proposed detector outperforms baseline detectors on real-world datasets while improving interpretability and robustness in data scarcity scenarios. |
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| Challenge: | Existing video fake news detection benchmarks focus on the detection accuracy, while failing to provide fine-grained assessments for the entire detection process. |
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| Challenge: | Existing methods for detecting fake news videos fall short due to lack of knowledge to verify the news is real or not. |
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| Challenge: | Existing methods for short video fake news detection ignore the implicit opinions and evolving nature of opinions across modalities. |
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| Challenge: | Existing methods for detecting fake news are limited due to non-transparent reasoning processes and inherent risks of integration with large language models. |
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Dialectical Structured Reasoning for Explainable Multimodal Fake News Detection (2026.findings-acl)
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Ruichao Yang, Yufan Bian, Wei Gao, Bo-Wen Zhang, Jing Ma, Hongzhan Lin, Ziyang Luo, Xiaobin Zhu, Xu-Cheng Yin
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Adapting Fake News Detection to the Era of Large Language Models (2024.findings-naacl)
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| Challenge: | a gap exists in understanding the interplay between machine-paraphrased real news, machine-generated fake news, and human-written real news . false information is easier to generate but harder to detect due to the bias of detectors against machine-generated texts . |
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| Challenge: | Existing methods for fake news detection focus on fact-checked reports, resulting in limited coverage and debunking delays. |
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| Challenge: | Existing frameworks for detecting fake news videos are limited . a new approach is proposed to integrate neighborhood information of new videos . |
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| Challenge: | Despite advances in large language models, their application to misinformation detection remains hindered by issues of logical inconsistency and superficial verification. |
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Event-Radar: Event-driven Multi-View Learning for Multimodal Fake News Detection (2024.acl-long)
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| Challenge: | Existing methods for detecting multimedia fake news have demonstrated excellent results . however, addressing event-level inconsistency and learning from poor-quality news remains a challenge . |
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