3 papers
cs.LG2026
When Normality Shifts: Risk-Aware Test-Time Adaptation for Unsupervised Tabular Anomaly Detection
Wei Huang, Hezhe Qiao, Kailai Zhang +3
Unsupervised tabular anomaly detection methods typically learn feature patterns from normal samples during training and subsequently identify samples that deviate from these patter…
cs.CR2025
Feint and Attack: Attention-Based Strategies for Jailbreaking and Protecting LLMs
Rui Pu, Chaozhuo Li, Rui Ha +5
Jailbreak attack can be used to access the vulnerabilities of Large Language Models (LLMs) by inducing LLMs to generate the harmful content. And the most common method of the attac…
cs.AI2025
Fact in Fragments: Deconstructing Complex Claims via LLM-based Atomic Fact Extraction and Verification
Liwen Zheng, Chaozhuo Li, Zheng Liu +4
Fact verification plays a vital role in combating misinformation by assessing the veracity of claims through evidence retrieval and reasoning. However, traditional methods struggle…