Papers by Xiangzheng Kong
IMOL: Incomplete-Modality-Tolerant Learning for Multi-Domain Fake News Video Detection (2025.acl-long)
Copied to clipboard
| Challenge: | Existing methods for fake news video detection focus on a specific domain and assume multiple modalities. |
| Approach: | They propose an incomplete-modality-tolerant learning framework for fake news video detection . they use cross-modal consistency to reconstruct missing modalities and transferable knowledge through cross-sample reasoning . |
| Outcome: | The proposed framework improves performance and robustness of multi-domain fake news video detection while generalizing to unseen domains under incomplete modality conditions. |
From Detection to Understanding: Multi-Turn Reasoning for Video Misinformation Analysis (2026.acl-long)
Copied to clipboard
| Challenge: | Existing benchmarks focus on binary veracity judgments and do not evaluate process-level justifications for misinformation models. |
| Approach: | They propose a video misinformation analysis benchmark that assesses reasoning in video misinterpretation. |
| Outcome: | The proposed framework improves reasoning accuracy and explanation quality compared to existing models . it covers 12 fine-grained deception categories and progresses from perceptual attribution to intent and persuasion analysis. |
From What Is Said to Why It Is Framed: Intent-Aware News Video Understanding (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing verification methods for short-form news videos neglect communicative intent . stylistic presentation and factual manipulation are often intertwined, resulting in shortcut learning . |
| Approach: | They propose a theory-grounded representation of communicative intent that captures creator stance, audience need activation, and communication strategy. |
| Outcome: | The proposed framework captures creator stance, audience need activation, and communication strategy. |