Labelbox has introduced new features to its video editor aimed at enhancing data labeling visibility and efficiency, particularly for tasks related to generative AI video projects such as text-to-video and video captioning. Among the updates is the ability to create deeply nested classifications, allowing users to organize and analyze video data with greater precision by establishing complex hierarchies that mirror real-world scenarios. The editor now also supports visualizing classifications directly on the timeline, facilitating easier editing and rearrangement of labels. Additional features include the ability to skip a specified number of frames, which is particularly useful for annotating longer videos, and improvements to the toggle function for classifications. These enhancements are designed to provide flexibility, accuracy, and efficiency in video labeling, reflecting Labelbox's commitment to continuous improvement based on customer feedback.