most citedMARE: Multimodal Alignment and Reinforcement for Explainable Deepfake Detection via Vision-Language Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2026

HumanForge: A Human-Centric Deepfake Video Benchmark with Multi-Agent Forgery Rationales

Wenbo Xu, Zhimin Chen, Xiaojie Liang +3

Rapid advancements in video diffusion models and temporal editing tools have enabled the generation of highly realistic human-centric videos, presenting unprecedented challenges to…

cs.CR2026

Geometry-Aware Localized Watermarking for Copyright Protection in Embedding-as-a-Service

Zhimin Chen, Xiaojie Liang, Wenbo Xu +2

Embedding-as-a-Service (EaaS) has become an important semantic infrastructure for natural language and multimedia applications, but it is highly vulnerable to model stealing and co…

cs.CV20261 cited

MARE: Multimodal Alignment and Reinforcement for Explainable Deepfake Detection via Vision-Language Models

Wenbo Xu, Wei Lu, Xiangyang Luo +1

Deepfake detection is a widely researched topic that is crucial for combating the spread of malicious content, with existing methods mainly modeling the problem as classification o…

cs.CV2025

Weakly Supervised Multimodal Temporal Forgery Localization via Multitask Learning

Wenbo Xu, Wei Lu, Xiangyang Luo

The spread of Deepfake videos has caused a trust crisis and impaired social stability. Although numerous approaches have been proposed to address the challenges of Deepfake detecti…

cs.CV2025

A Multimodal Deviation Perceiving Framework for Weakly-Supervised Temporal Forgery Localization

Wenbo Xu, Junyan Wu, Wei Lu +2

Current researches on Deepfake forensics often treat detection as a classification task or temporal forgery localization problem, which are usually restrictive, time-consuming, and…

cs.SD2025

Weakly-supervised Audio Temporal Forgery Localization via Progressive Audio-language Co-learning Network

Junyan Wu, Wenbo Xu, Wei Lu +3

Audio temporal forgery localization (ATFL) aims to find the precise forgery regions of the partial spoof audio that is purposefully modified. Existing ATFL methods rely on training…