3 accepted papers
Point cloud semantic segmentation is fundamental to 3D scene understanding, but dense annotation requirements limit scalability. Although recent label propagation and contrastive learning methods enhance local consistency, the incomplete object coverage caused by sparse annotations hinders global c
Large-scale foundation models provide powerful feature representations for downstream object segmentation tasks. However, when adapted to specific tasks through the full-parameter fine-tuning, the enormous parameters being updated often results in significant computational overhead, creating a bottl…
Large Language Models (LLMs) increasingly employ alignment techniques to prevent harmful outputs. Despite these safeguards, attackers can circumvent them by crafting prompts that induce LLMs to generate harmful content. Current methods typically target exact affirmative responses, suffering from lim…