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The Open VLM Leaderboard is a data visualization tool designed to showcase the performance and results of various Vision-Language Models (VLMs). It serves as a centralized platform where users can explore and compare evaluation metrics of different VLMs across multiple datasets and tasks.
• Comprehensive Results Collection: Aggregates performance metrics from a wide range of VLM models and datasets.
• Interactive Filters: Enables users to filter results by model type, dataset, or evaluation metric.
• Customizable Visualizations: Provides detailed charts and graphs to help users understand model performance.
• Real-Time Updates: Reflects the latest evaluation results as new models or datasets are added.
• Bleaderboard Comparisons: Highlights top-performing models across different tasks and datasets.
What is the purpose of the Open VLM Leaderboard?
The Open VLM Leaderboard aims to provide a transparent and accessible platform for comparing the performance of various Vision-Language Models across different datasets and tasks.
How are models selected for inclusion on the leaderboard?
Models are included based on their publicly available evaluation results. The leaderboard aggregates data from a variety of sources to ensure a comprehensive view of model performance.
How often is the leaderboard updated?
The leaderboard is updated periodically to include new models and datasets as they become available. Users are encouraged to check back regularly for the latest information.