6 papers
Safe Semantics, Unsafe Interpretations: Tackling Implicit Reasoning Safety in Large Vision-Language Models
Wei Cai, Jian Zhao, Yuchu Jiang +2
Large Vision-Language Models face growing safety challenges with multimodal inputs. This paper introduces the concept of Implicit Reasoning Safety, a vulnerability in LVLMs. Benign…
ERF-BA-TFD+: A Multimodal Model for Audio-Visual Deepfake Detection
Xin Zhang, Jiaming Chu, Jian Zhao +5
Deepfake detection is a critical task in identifying manipulated multimedia content. In real-world scenarios, deepfake content can manifest across multiple modalities, including au…
Butter: Frequency Consistency and Hierarchical Fusion for Autonomous Driving Object Detection
Xiaojian Lin, Wenxin Zhang, Yuchu Jiang +7
Hierarchical feature representations play a pivotal role in computer vision, particularly in object detection for autonomous driving. Multi-level semantic understanding is crucial…
Loupe: A Generalizable and Adaptive Framework for Image Forgery Detection
Yuchu Jiang, Jiaming Chu, Jian Zhao +5
The proliferation of generative models has raised serious concerns about visual content forgery. Existing deepfake detection methods primarily target either image-level classificat…
Mimic In-Context Learning for Multimodal Tasks
Yuchu Jiang, Jiale Fu, Chenduo Hao +4
Recently, In-context Learning (ICL) has become a significant inference paradigm in Large Multimodal Models (LMMs), utilizing a few in-context demonstrations (ICDs) to prompt LMMs f…
Fast Large Language Model Collaborative Decoding via Speculation
Jiale Fu, Yuchu Jiang, Junkai Chen +3
Large Language Model (LLM) collaborative decoding techniques improve output quality by combining the outputs of multiple models at each generation step, but they incur high computa…