16 papers
Not Every Cue Is Evidence: Cue Supportability for Forensic Distillation in Face Forgery Detection
Binjia Zhou, Dawei Luo, Shuai Chen +7
Explainable face forgery detection requires not only correct judgments but also forensic evidence supported by the input image. However, training cues are typically derived from th…
Structured Local Differential Modeling for AI-Generated Image Detection
Jiazhen Yang, Ruijin Jin, Junjun Zheng +3
The rapid advancement of AI-generated content has made the reliable detection of generated images an increasingly critical challenge. Existing detection methods are often dominated…
Mitigating Many-shot Jailbreak Attacks with One Single Demonstration
Kejia Chen, Jiawen Zhang, Boheng Li +6
Many-shot jailbreaking (MSJ) causes safety-aligned language models to answer harmful queries by preceding them with many harmful question-answer demonstrations. We study why this a…
Confidence-Aware Alignment Makes Reasoning LLMs More Reliable
Kejia Chen, Jiawen Zhang, Yihong Wu +5
Large reasoning models often reach correct answers through flawed intermediate steps, creating a gap between final accuracy and reasoning reliability. Existing alignment strategies…
Adaptive Forensic Feature Refinement via Intrinsic Importance Perception
Jiazhen Yang, Junjun Zheng, Kejia Chen +5
With the rapid development of generative models and multimodal content editing technologies, the key challenge in synthetic image detection (SID) lies in cross-distribution general…
-RSMDE: 40 Faster and High-Fidelity Remote Sensing Monocular Depth Estimation
Ruizhi Wang, Weihan Li, Zunlei Feng +5
Real-time, high-fidelity monocular depth estimation from remote sensing imagery is crucial for numerous applications, yet existing methods face a stark trade-off between accuracy a…
EvolveReason: Self-Evolving Reasoning Paradigm for Explainable Deepfake Facial Image Identification
Binjia Zhou, Dawei Luo, Shuai Chen +7
With the rapid advancement of AIGC technology, developing identification methods to address the security challenges posed by deepfakes has become urgent. Face forgery identificatio…
SpatCode: Rotary-based Unified Encoding Framework for Efficient Spatiotemporal Vector Retrieval
Bingde Hu, Enhao Pan, Wanjing Zhou +3
Spatiotemporal vector retrieval has emerged as a critical paradigm in modern information retrieval, enabling efficient access to massive, heterogeneous data that evolve over both t…
Token-Level Inference-Time Alignment for Vision-Language Models
Kejia Chen, Jiawen Zhang, Jiacong Hu +4
Vision-Language Models (VLMs) have become essential backbones of modern multimodal intelligence, yet their outputs remain prone to hallucination-plausible text misaligned with visu…
RS3DBench: A Comprehensive Benchmark for 3D Spatial Perception in Remote Sensing
Jiayu Wang, Ruizhi Wang, Jie Song +4
In this paper, we introduce a novel benchmark designed to propel the advancement of general-purpose, large-scale 3D vision models for remote sensing imagery. While several datasets…
CorrDetail: Visual Detail Enhanced Self-Correction for Face Forgery Detection
Binjia Zhou, Hengrui Lou, Lizhe Chen +6
With the swift progression of image generation technology, the widespread emergence of facial deepfakes poses significant challenges to the field of security, thus amplifying the u…
Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models
Kejia Chen, Jiawen Zhang, Jiacong Hu +4
Quantized large language models (LLMs) have gained increasing attention and significance for enabling deployment in resource-constrained environments. However, emerging studies on…
Reinforced Model Merging
Jiaqi Han, Jingwen Ye, Shunyu Liu +4
The success of large language models has garnered widespread attention for model merging techniques, especially training-free methods which combine model capabilities within the pa…
Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis
Shengxuming Zhang, Weihan Li, Tianhong Gao +6
Pathological diagnosis is vital for determining disease characteristics, guiding treatment, and assessing prognosis, relying heavily on detailed, multi-scale analysis of high-resol…
Fire and Smoke Detection with Burning Intensity Representation
Xiaoyi Han, Yanfei Wu, Nan Pu +4
An effective Fire and Smoke Detection (FSD) and analysis system is of paramount importance due to the destructive potential of fire disasters. However, many existing FSD methods di…
Benchmarking Multi-Scene Fire and Smoke Detection
Xiaoyi Han, Nan Pu, Zunlei Feng +4
The current irregularities in existing public Fire and Smoke Detection (FSD) datasets have become a bottleneck in the advancement of FSD technology. Upon in-depth analysis, we iden…