activity
20222025
most citedDensePure: Understanding Diffusion Models towards Adversarial Robustness

18 citations · 19 across the 2 of their papers we have counts for

collaborators

5 papers

cs.AI2025

Reinforcement Learning for Self-Improving Agent with Skill Library

Jiongxiao Wang, Qiaojing Yan, Yawei Wang +6

Large Language Model (LLM)-based agents have demonstrated remarkable capabilities in complex reasoning and multi-turn interactions but struggle to continuously improve and adapt wh…

cs.CV2025

Robust Representation Consistency Model via Contrastive Denoising

Jiachen Lei, Julius Berner, Jiongxiao Wang +5

Robustness is essential for deep neural networks, especially in security-sensitive applications. To this end, randomized smoothing provides theoretical guarantees for certifying ro…

cs.CR20241 cited

FATH: Authentication-based Test-time Defense against Indirect Prompt Injection Attacks

Jiongxiao Wang, Fangzhou Wu, Wendi Li +5

Large language models (LLMs) have been widely deployed as the backbone with additional tools and text information for real-world applications. However, integrating external informa…

cs.CV2024

Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset

Yingzi Ma, Jiongxiao Wang, Fei Wang +10

Machine unlearning has emerged as an effective strategy for forgetting specific information in the training data. However, with the increasing integration of visual data, privacy c…

cs.LG202218 cited

DensePure: Understanding Diffusion Models towards Adversarial Robustness

Chaowei Xiao, Zhongzhu Chen, Kun Jin +6

Diffusion models have been recently employed to improve certified robustness through the process of denoising. However, the theoretical understanding of why diffusion models are ab…