From the 2 of 20 linked papers with an AI index.
13 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…
SafeNexus: Discovering and Steering Modality-Universal Safety Neurons in MLLMs
Jian Yu, Fei Shen, Cong Wang +6
Although Large Language Models (LLMs) have demonstrated promising safety performance, extending them to Multimodal Large Language Models (MLLMs) exposes a significant gap between e…
LaP-Forensics: Latent-Pixel Consistency Guided Multimodal Reasoning for Deepfake Detection
Can Wang, Yuhao Wang, Yushe Cao +2
Recent generative models can produce images with few obvious visual artifacts, weakening detectors and explanations that rely only on surface appearance. We present LaP-Forensics,…
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…
Targeted Interpretable Safety Neuron Enhancement for Multilingual Vision-Language Large Models
Enyi Shi, Fei Shen, Shuyi Miao +5
With the widespread deployment of vision-language large models (VLLMs), their safety alignment faces dual challenges across languages and modalities. Existing methods model multili…