Y. Ong

Experiments across synthetic benchmarks and a real-world robot arm control problem, together with evaluations under different acquisition functions and evolutionary multitasking, demonstrate the effectiveness and generality of ICG-MTO for few-shot multitask optimization.

Adversarial training can be made more effective by considering the hierarchical relationships between classes, leading to vision-language models that are more robust to attacks on both specific classes and their broader categories.