Limited Query

Limited query research focuses on efficiently solving problems with minimal data access, a crucial aspect in scenarios with resource constraints or privacy concerns. Current efforts concentrate on improving the accuracy of tasks like image segmentation and question answering using only a small number of queries, employing techniques such as generative adversarial networks (GANs) and novel voting mechanisms to enhance performance. These advancements have significant implications for improving the robustness and efficiency of machine learning models, particularly in black-box attack scenarios and applications where obtaining labeled data is expensive or impractical.