8 papers · 1 filter
V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors
Shichao Kan, Chengpeng Hong, Jingtong Dou +8
As generated videos become increasingly realistic, reliable video forgery detection is increasingly important. Existing studies typically optimize and use video forgery detectors a…
Decodable Is Not Grounded: A Vision-Ablation Arbiter for VLM Spatial Reasoning
Chih-Ting Liao, Fei Shen, Xin Cao +1
The standard way to read latent knowledge out of a model, a linear probe confirmed by a steering recovery, can systematically overstate what a vision-language model (VLM) actually…
Latent Anomaly Knowledge Excavation: Unveiling Sparse Sensitive Neurons in Vision-Language Models
Shaotian Li, Shangze Li, Chuancheng Shi +5
Large-scale vision-language models (VLMs) exhibit remarkable zero-shot capabilities, yet the internal mechanisms driving their anomaly detection (AD) performance remain poorly unde…
Beyond Surface Artifacts: Capturing Shared Latent Forgery Knowledge Across Modalities
Jingtong Dou, Chuancheng Shi, Jian Wang +3
As generative artificial intelligence evolves, deepfake attacks have escalated from single-modality manipulations to complex, multimodal threats. Existing forensic techniques face…
Who Transfers Safety? Identifying and Targeting Cross-Lingual Shared Safety Neurons
Xianhui Zhang, Chengyu Xie, Linxia Zhu +6
Multilingual safety remains significantly imbalanced, leaving non-high-resource (NHR) languages vulnerable compared to robust high-resource (HR) ones. Moreover, the neural mechanis…
TraceRouter: Robust Safety for Large Foundation Models via Path-Level Intervention
Chuancheng Shi, Shangze Li, Wenjun Lu +5
Despite their capabilities, large foundation models (LFMs) remain susceptible to adversarial manipulation. Current defenses predominantly rely on the "locality hypothesis", suppres…