Work

From Form to Logic: Masked Reconstruction and Reasoning Distillation for Short Video Fake News Detection

Year: 2026

Type: conference-paper

Abstract: The rapid growth of short video platforms has made multimodal fake news more prevalent.Existing detectors suffer from two major limitations: (I) global-alignment bias that overemphasizes holistic cross-modal matching and thus misses subtle, localized inconsistencies; and (II) LLM-based methods that leverage powerful generative reasoning to identify cognitive forgeries but inherently suffer from hallucinations and high inference latency.To overcome these limitations, we propose PCDD, a novel Perception-Cognition Dualdriven Detector that jointly observes the form and probes the logic for short video fake news detection.The perception stream exposes finegrained cross-modal conflicts by amplifying localized inconsistencies into explicit discrepancies.The cognition stream transfers reasoning capabilities from LLMs to a lightweight student to mine cognitive forgeries, while reducing the risk of hallucinations and eliminating reliance on LLMs at inference.Experiments on real-world datasets show that PCDD consistently outperforms baselines, while improving interpretability and robustness in data scarcity scenarios.

Source: Proceedings of the conference - Association for Computational Linguistics. Meeting

DOI: 10.18653/v1/2026.acl-long.579

Authors: Qingyan Wang, Lianwei Wu, Botao Wang, Wangkang, Yaxiong Wang

Institutions: Northwestern Polytechnical University, Hefei University of Technology

Language: English

Topic: Misinformation and Its Impacts

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

Open Access status: hybrid

Funders: National Natural Science Foundation of China, Basic and Applied Basic Research Foundation of Guangdong Province

Awards: G192882225, G8863109806