1 citations · 2 across the 17 of their papers we have counts for
19 papers
SynMark: Semantic-Coordinate Multi-Bit Watermarking during LLM Code Generation
Rui Xu, Weizhi Liu, Zhaoxia Yin
LLM-generated code is increasingly reused across downstream applications and often undergoes identifier renaming or structural refactoring, making robustness to functionality-prese…
Trace, Verify, and Correct: A Training-Free Framework for Spatial Reasoning in Multimodal LLMs
Yang Yang, Jiawei Chen, Tairan Chen +1
Although Multimodal Large Language Models (MLLMs) have made substantial progress, their spatial reasoning may still produce intermediate judgments inconsistent with the input image…
VertMark: A Unified Training-Free Robust Watermarking Framework for Vertical Domain Pre-trained Language Models
Cong Kong, Xin Cheng, Zhaoxia Yin +3
With the application of vertical domain pre-trained language models (VPLMs) in specialized fields such as medical, finance, and law, model parameters and inference capabilities hav…
Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO
Yu Tian, Jiawei Chen, Lifan Zheng +5
We introduce Skills-Coach, a novel automated framework designed to significantly enhance the self-evolution of skills within Large Language Model (LLM)-based agents. Addressing the…
DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models
JiYang Wang, Jiawei Chen, Mengqi Xiao +3
Object level hallucination remains a central reliability challenge for vision language models (VLMs), particularly in binary object existence verification. Existing benchmarks emph…
LCO: LLM-based Constraint Optimization for Safer Agentic LLMs in Real-world Tasks
Jiayong Wan, Jiawei Chen, Zhaoxia Yin +2
Large Language Models (LLMs) are increasingly acting as autonomous agents, but their continuous interaction with the environment can lead to in-context reward hacking (ICRH), a phe…
Tex3D: Objects as Attack Surfaces via Adversarial 3D Textures for Vision-Language-Action Models
Jiawei Chen, Simin Huang, Jiawei Du +5
Vision-language-action (VLA) models have shown strong performance in robotic manipulation, yet their robustness to physically realizable adversarial attacks remains underexplored.…
Face-D(^2)CL: Multi-Domain Synergistic Representation with Dual Continual Learning for Facial DeepFake Detection
Yushuo Zhang, Yu Cheng, Yongkang Hu +3
Facial forgery techniques are advancing rapidly, posing severe threats to public trust and information security while imposing higher demands on the continual adaptation of DeepFak…
Adversarial Attacks on Medical Hyperspectral Imaging Exploiting Spectral-Spatial Dependencies and Multiscale Features
Yunrui Gu, Zhenzhe Gao, Cong Kong +2
Medical hyperspectral imaging (MHSI) has shown strong potential for disease diagnosis by capturing spectral-spatial information of tissues. While deep learning has substantially im…
Who Can See Through You? Adversarial Shielding Against VLM-Based Attribute Inference Attacks
Yucheng Fan, Jiawei Chen, Yu Tian +1
As vision-language models (VLMs) become widely adopted, VLM-based attribute inference attacks have emerged as a serious privacy concern, enabling adversaries to infer private attri…
Red Teaming Large Reasoning Models
Jiawei Chen, Yang Yang, Chao Yu +6
Large Reasoning Models (LRMs) have emerged as a powerful advancement in multi-step reasoning tasks, offering enhanced transparency and logical consistency through explicit chains o…
KG-DF: A Black-box Defense Framework against Jailbreak Attacks Based on Knowledge Graphs
Shuyuan Liu, Jiawei Chen, Xiao Yang +2
With the widespread application of large language models (LLMs) in various fields, the security challenges they face have become increasingly prominent, especially the issue of jai…
CLASP: Training-Free LLM-Assisted Source Code Watermarking via Semantic-Preserving Transformations
Rui Xu, Jiawei Chen, Weizhi Liu +3
The proliferation of open-source code and large language models (LLMs) for code generation has amplified the risks of unauthorized reuse and intellectual property infringement. Sou…
Exploring the Secondary Risks of Large Language Models
Jiawei Chen, Zhengwei Fang, Yu Tian +4
Ensuring the safety and alignment of Large Language Models is a significant challenge with their growing integration into critical applications and societal functions. While prior…
RFNNS: Robust Fixed Neural Network Steganography with Universal Text-to-Image Models
Yu Cheng, Jiuan Zhou, Jiawei Chen +2
With the rapid development of generative AI, image steganography has garnered widespread attention due to its unique concealment. Recent studies have demonstrated the practical adv…
Protecting Copyright of Medical Pre-trained Language Models: Training-Free Backdoor Model Watermarking
Cong Kong, Rui Xu, Weixi Chen +2
With the advancement of intelligent healthcare, medical pre-trained language models (Med-PLMs) have emerged and demonstrated significant effectiveness in downstream medical tasks.…
AutoBreach: Universal and Adaptive Jailbreaking with Efficient Wordplay-Guided Optimization
Jiawei Chen, Xiao Yang, Zhengwei Fang +4
Despite the widespread application of large language models (LLMs) across various tasks, recent studies indicate that they are susceptible to jailbreak attacks, which can render th…
Exploring the Robustness of Decision-Level Through Adversarial Attacks on LLM-Based Embodied Models
Shuyuan Liu, Jiawei Chen, Shouwei Ruan +2
Embodied intelligence empowers agents with a profound sense of perception, enabling them to respond in a manner closely aligned with real-world situations. Large Language Models (L…
FaceCat: Enhancing Face Recognition Security with a Unified Diffusion Model
Jiawei Chen, Xiao Yang, Yinpeng Dong +2
Face anti-spoofing (FAS) and adversarial detection (FAD) have been regarded as critical technologies to ensure the safety of face recognition systems. However, due to limited pract…