3 citations · 5 across the 4 of their papers we have counts for
4 papers
SoK: Robustness in Large Language Models against Jailbreak Attacks
Feiyue Xu, Hongsheng Hu, Chaoxiang He +9
Large Language Models (LLMs) have achieved remarkable success but remain highly susceptible to jailbreak attacks, in which adversarial prompts coerce models into generating harmful…
Robust Prediction when Features are Missing
Xiuming Liu, Dave Zachariah, Petre Stoica
Predictors are learned using past training data which may contain features that are unavailable at the time of prediction. We develop an approach that is robust against outlying mi…
Reliable Semi-Supervised Learning when Labels are Missing at Random
Xiuming Liu, Dave Zachariah, Johan Wågberg +1
Semi-supervised learning methods are motivated by the availability of large datasets with unlabeled features in addition to labeled data. Unlabeled data is, however, not guaranteed…
Composite Gaussian Processes: Scalable Computation and Performance Analysis
Xiuming Liu, Dave Zachariah, Edith C. H. Ngai
Gaussian process (GP) models provide a powerful tool for prediction but are computationally prohibitive using large data sets. In such scenarios, one has to resort to approximate m…