20 citations · 54 across the 12 of their papers we have counts for
12 papers
PromptFix: Few-shot Backdoor Removal via Adversarial Prompt Tuning
Tianrong Zhang, Zhaohan Xi, Ting Wang +2
Pre-trained language models (PLMs) have attracted enormous attention over the past few years with their unparalleled performances. Meanwhile, the soaring cost to train PLMs as well…
On the Difficulty of Defending Contrastive Learning against Backdoor Attacks
Changjiang Li, Ren Pang, Bochuan Cao +4
Recent studies have shown that contrastive learning, like supervised learning, is highly vulnerable to backdoor attacks wherein malicious functions are injected into target models,…
Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks
Zhaohan Xi, Tianyu Du, Changjiang Li +5
Pre-trained language models (PLMs) have demonstrated remarkable performance as few-shot learners. However, their security risks under such settings are largely unexplored. In this…
On the Security Risks of Knowledge Graph Reasoning
Zhaohan Xi, Tianyu Du, Changjiang Li +6
Knowledge graph reasoning (KGR) -- answering complex logical queries over large knowledge graphs -- represents an important artificial intelligence task, entailing a range of appli…
Neural Architectural Backdoors
Ren Pang, Changjiang Li, Zhaohan Xi +2
This paper asks the intriguing question: is it possible to exploit neural architecture search (NAS) as a new attack vector to launch previously improbable attacks? Specifically, we…
An Embarrassingly Simple Backdoor Attack on Self-supervised Learning
Changjiang Li, Ren Pang, Zhaohan Xi +4
As a new paradigm in machine learning, self-supervised learning (SSL) is capable of learning high-quality representations of complex data without relying on labels. In addition to…
Reasoning over Multi-view Knowledge Graphs
Zhaohan Xi, Ren Pang, Changjiang Li +4
Recently, knowledge representation learning (KRL) is emerging as the state-of-the-art approach to process queries over knowledge graphs (KGs), wherein KG entities and the query are…
Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era
Changjiang Li, Li Wang, Shouling Ji +4
Facial Liveness Verification (FLV) is widely used for identity authentication in many security-sensitive domains and offered as Platform-as-a-Service (PaaS) by leading cloud vendor…
Towards Robust Reasoning over Knowledge Graphs
Zhaohan Xi, Ren Pang, Changjiang Li +4
Answering complex logical queries over large-scale knowledge graphs (KGs) represents an important artificial intelligence task, entailing a range of applications. Recently, knowled…
On the Security Risks of AutoML
Ren Pang, Zhaohan Xi, Shouling Ji +2
Neural Architecture Search (NAS) represents an emerging machine learning (ML) paradigm that automatically searches for models tailored to given tasks, which greatly simplifies the…
TrojanZoo: Towards Unified, Holistic, and Practical Evaluation of Neural Backdoors
Ren Pang, Zheng Zhang, Xiangshan Gao +5
Neural backdoors represent one primary threat to the security of deep learning systems. The intensive research has produced a plethora of backdoor attacks/defenses, resulting in a…
Graph Backdoor
Zhaohan Xi, Ren Pang, Shouling Ji +1
One intriguing property of deep neural networks (DNNs) is their inherent vulnerability to backdoor attacks -- a trojan model responds to trigger-embedded inputs in a highly predict…