activity
20232026
most citedFLTracer: Accurate Poisoning Attack Provenance in Federated Learning

1 citations · 1 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CL2026

Before Agent Tells The Lie: Has Deception Already Been Represented?

Xinling Li, Dadi Guo, Qingyu Liu +5

Large language model (LLM)-based agents can exhibit deceptive behavior during task execution, including hiding failures, fabricating results, or falsely signaling task completion.…

cs.CR2026

ClashBench: Conflicts Leading Agents to Seize and Harm

Yuejin Xie, Yu Li, Dadi Guo +6

As agent systems become more widely used, multiple agent sessions increasingly run alongside pre-existing user tasks in the same environment, sharing resources with limited capacit…

cs.AI2026

SafeEvolve: Harness-Policy Co-Evolution from Agent Experience for Safety Alignment

Qinghua Mao, Wanying Qu, Dadi Guo +8

The performance of LLM-based agents is jointly shaped by the base model and the harness used when interacting with the environment. This exposes them to safety risks in both harmfu…

cs.AI2026

SHE: Trajectory-driven Safety Harness Evolution for LLM Agents

Wanying Qu, Qinghua Mao, Yu Li +12

The safety of large language model (LLM) agents depends not only on model weights but also on the agent harness that manages context, memory, tools, permissions, and runtime contro…

cs.AI2026

AgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Security

Dongrui Liu, Yu Li, Zhonghao Yang +47

Modern open-world agents such as OpenClaw exhibit powerful cross-environment execution capabilities yet introduce broad new safety risk sources. Meanwhile, advanced frontier AI mod…

cs.CL2026

Code2Math: Can Your Code Agent Evolve Math Problems Through Exploration?

Dadi Guo, Yuejin Xie, Qingyu Liu +11

As large language models (LLMs) advance their mathematical capabilities toward the IMO and research level, the scarcity of challenging, high-quality problems has become a significa…

cs.CV2026

RBD: A Reconstruction-Based Method for Generalizable and Efficient Detection of Fake Images

Qingyu Liu, Zhongjie Ba, Jianmin Guo +4

Recently, reconstruction-based methods have gained attention for AIGC image detection. These methods leverage pre-trained diffusion models to reconstruct inputs and measure residua…

cs.CR2026

Attack-Resistant Watermarking for AIGC Image Forensics via Diffusion-based Semantic Deflection

Qingyu Liu, Yitao Zhang, Zhongjie Ba +4

Protecting the copyright of user-generated AI images is an emerging challenge as AIGC becomes pervasive in creative workflows. Existing watermarking methods (1) remain vulnerable t…

cs.AI2026

AgentDoG: A Diagnostic Guardrail Framework for AI Agent Safety and Security

Dongrui Liu, Qihan Ren, Chen Qian +40

The rise of AI agents introduces complex safety and security challenges arising from autonomous tool use and environmental interactions. Current guardrail models lack agentic risk…

cs.AI2025

Are Your Agents Upward Deceivers?

Dadi Guo, Qingyu Liu, Dongrui Liu +13

Large Language Model (LLM)-based agents are increasingly used as autonomous subordinates that carry out tasks for users. This raises the question of whether they may also engage in…

cs.CV2024

Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection

Zhongjie Ba, Qingyu Liu, Zhenguang Liu +4

Deepfake technology has given rise to a spectrum of novel and compelling applications. Unfortunately, the widespread proliferation of high-fidelity fake videos has led to pervasive…

cs.CR2023★ 1 cited

FLTracer: Accurate Poisoning Attack Provenance in Federated Learning

Xinyu Zhang, Qingyu Liu, Zhongjie Ba +5

Federated Learning (FL) is a promising distributed learning approach that enables multiple clients to collaboratively train a shared global model. However, recent studies show that…