12 citations · 28 across the 35 of their papers we have counts for
11 papers · 1 filter
PSRT: Accelerating LRM-based Guard Models via Prefilled Safe Reasoning Traces
Jiawei Zhao, Yuang Qi, Weiming Zhang +2
Large Reasoning Models (LRMs) have demonstrated remarkable performance on tasks such as mathematics and code generation. Motivated by these strengths, recent work has empirically d…
Multimodal Prompt Decoupling Attack on the Safety Filters in Text-to-Image Models
Xingkai Peng, Jun Jiang, Meng Tong +4
Text-to-image (T2I) models have been widely applied in generating high-fidelity images across various domains. However, these models may also be abused to produce Not-Safe-for-Work…
ScaleCap: Inference-Time Scalable Image Captioning via Dual-Modality Debiasing
Long Xing, Qidong Huang, Xiaoyi Dong +10
This paper presents ScaleCap, an inference-time scalable image captioning strategy that generates comprehensive and detailed image captions. The key challenges of high-quality imag…
TAG-WM: Tamper-Aware Generative Image Watermarking via Diffusion Inversion Sensitivity
Yuzhuo Chen, Zehua Ma, Han Fang +2
AI-generated content (AIGC) enables efficient visual creation but raises copyright and authenticity risks. As a common technique for integrity verification and source tracing, digi…
BinMetric: A Comprehensive Binary Analysis Benchmark for Large Language Models
Xiuwei Shang, Guoqiang Chen, Shaoyin Cheng +5
Binary analysis remains pivotal in software security, offering insights into compiled programs without source code access. As large language models (LLMs) continue to excel in dive…
CompileAgent: Automated Real-World Repo-Level Compilation with Tool-Integrated LLM-based Agent System
Li Hu, Guoqiang Chen, Xiuwei Shang +6
With open-source projects growing in size and complexity, manual compilation becomes tedious and error-prone, highlighting the need for automation to improve efficiency and accurac…
An Empirical Study on the Effectiveness of Large Language Models for Binary Code Understanding
Xiuwei Shang, Zhenkan Fu, Shaoyin Cheng +5
Binary code analysis plays a pivotal role in the field of software security and is widely used in tasks such as software maintenance, malware detection, software vulnerability disc…
Clean Image May be Dangerous: Data Poisoning Attacks Against Deep Hashing
Shuai Li, Jie Zhang, Yuang Qi +4
Large-scale image retrieval using deep hashing has become increasingly popular due to the exponential growth of image data and the remarkable feature extraction capabilities of dee…
MES-RAG: Bringing Multi-modal, Entity-Storage, and Secure Enhancements to RAG
Pingyu Wu, Daiheng Gao, Jing Tang +4
Retrieval-Augmented Generation (RAG) improves Large Language Models (LLMs) by using external knowledge, but it struggles with precise entity information retrieval. In this paper, w…
Beyond the Edge of Function: Unraveling the Patterns of Type Recovery in Binary Code
Gangyang Li, Xiuwei Shang, Shaoyin Cheng +5
Type recovery is a crucial step in binary code analysis, holding significant importance for reverse engineering and various security applications. Existing works typically simply t…
M3-AGIQA: Multimodal, Multi-Round, Multi-Aspect AI-Generated Image Quality Assessment
Chuan Cui, Kejiang Chen, Zhihua Wei +3
The rapid advancement of AI-generated image (AIGI) models presents new challenges for evaluating image quality, particularly across three aspects: perceptual quality, prompt corres…