For what purpose was the dataset created? To address this, we propose ViLCo-Bench. Who created the dataset(e.g., which team, research group) and on behalf of which Who funded the creation of the dataset? What do the instances that comprise the dataset represent (e.g., documents, photos, What data does each instance consist of? Is there a label or target associated with each instance?

This method allows API users to easily generate, discover, and mix and match image concepts without prior knowledge of how to prompt the model.

Additionally, real-time inference and generalization to large probe sets remains challenging.

Specifically, we learn the data representation as a task-specific composition of pre-trained token representations shared across all tasks. Then the correlations between different tasks' data representations are grounded

Current methods for identifying adversarial prompts aimed at "attacking" LLMs and eliciting undesirable outputs are limited by several factors.

The vast amount of data required to model wildfires at a larger scale presents difficulties in the collection and curation of the data.

Object tracking is a fundamental task in computer vision, requiring the localization of objects of interest across video frames.