Papers by Zongliang Han
Covariance Matrix-Driven Image Channel Allocation for Multimodal Fake News Detection (2026.findings-acl)
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| Challenge: | Existing methods focus on designing efficient multimodal fusion frameworks to bridge the semantic gap between images and texts. |
| Approach: | They propose a covariance matrix-driven image channel allocation method that expands the number of original channel maps and assigns importance scores to the expanded channel maps. |
| Outcome: | The proposed method achieves state-of-the-art on three public multimodal fake news detection benchmark datasets. |
Multi-Scale Spectral Selection and Entropy-Guided Uncertainty Fusion for Multimodal Rumor Detection (2026.findings-acl)
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| Challenge: | Existing methods for multimodal content detection fail to capture cross-modal semantic inconsistencies and ignore inherent noise in multimodal features. |
| Approach: | They propose a multimodal rumor detection method based on a frequency domain spectral selection method and entropy-guided uncertainty fusion method to capture cross-modal semantic inconsistencies. |
| Outcome: | The proposed method outperforms state-of-the-art methods in multimodal rumor detection . it shows stronger detection capability and robustness on multiple datasets . |