3 accepted papers
Existing Programming-By-Example (PBE) systems often rely on simplified benchmarks that fail to capture the high structural complexity—such as deeper nesting and frequent Unions—of real-world regexes. To overcome the resulting performance drop, we propose ReSyn, a synthesizer-agnostic divide-and-conq
The Vision Transformer (ViT) has surpassed Convolutional Neural Networks (CNNs) in performance, becoming the de facto architecture in modern computer vision. However, despite its superior representational capacity, research on the adversarial robustness of ViTs remains limited, with most studies sti
In this paper, we consider multi-objective reinforcement learning, which arises in many real-world problems with multiple optimization goals. We approach the problem with a max-min framework focusing on fairness among the multiple goals and develop a relevant theory and a practical model-free algori…