1 citations · 1 across the 6 of their papers we have counts for
10 papers
Is This Your Agent? Identity Watermarking for Agent Systems in Dynamic Environments
Yuwei Zhong, Yu Cheng, Jiuan Zhou +5
Agent systems deployed in dynamic environments continuously update their memories, skills, and runtime configurations, leading to evolving trajectories and challenges for persisten…
Safe-FCL: Continual Risk Awareness and Fine-Grained Safety Aggregation for Federated Continual Learning of LLMs
Shuaijie Ma, Yongkang Hu, Yu Cheng +4
Federated fine-tuning enables large language models (LLMs) to learn collaboratively from distributed client data, but malicious client updates can compromise global model safety. A…
SafeCoEvo: Co-Evolving Safety Harnesses and Guards for LLM Agents at Test-Time
Yu Cheng, Yongkang Hu, Shuaijie Ma +12
LLM agents deployed in real-world environments continually encounter new tasks and safety risks, while execution feedback typically becomes available only after each task is comple…
TI-StegoAlign: Channel-Guided Post-Training for Generative Text Steganography under Tokenization Inconsistency
Jiuan Zhou, Yuhao Xue, Yu Cheng +2
Generative text steganography enables LLM agents to exchange secret information through task-relevant messages. Yet most methods evaluate recovery on sender-side tokens, whereas th…
Benign in Isolation, Harmful in Composition: Security Risks in Agent Skill Ecosystems
Yi Xie, Jiawei Du, Yu Cheng +2
Skills are becoming the capability layer through which LLM agents turn plans into actions, but their use introduces security risks such as data leakage, unauthorized operations, an…
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…
TAME: A Trustworthy Test-Time Evolution of Agent Memory with Systematic Benchmarking
Yu Cheng, Yongkang Hu, Jiuan Zhou +8
Test-time evolution of agent memory represents a pivotal paradigm for advancing AGI, as it strengthens complex reasoning through experience accumulation without requiring parameter…
DTAMS: High-Capacity Generative Steganography via Dynamic Multi-Timestep Selection and Adaptive Deviation Mapping in Latent Diffusion
Yuhao Xue, Jiuan Zhou, Yu Cheng +1
With the rapid development of AIGC technologies, generative image steganography has attracted increasing attention due to its high imperceptibility and flexibility. However, existi…
Auto-Stega: An Agent-Driven System for Lifelong Strategy Evolution in LLM-Based Text Steganography
Jiuan Zhou, Yu Cheng, Yuan Xie +1
With the rapid progress of LLMs, high quality generative text has become widely available as a cover for text steganography. However, prevailing methods rely on hand-crafted or pre…
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…