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+ ---
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+ license: mit
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+ task_categories:
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+ - zero-shot-classification
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+ size_categories:
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+ - n<1K
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+ ---
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+
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+ # MMVP-VLM Benchmark Datacard
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+
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+ ## Basic Information
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+ **Title:** MMVP-VLM Benchmark
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+ **Description:** The MMVP-VLM (Multimodal Visual Patterns - Visual Language Models) Benchmark is designed to systematically evaluate the performance of recent CLIP-based models in understanding and processing visual patterns. It distills a subset of questions from the original MMVP benchmark into simpler language descriptions, categorizing them into distinct visual patterns. Each visual pattern is represented by 15 text-image pairs. The benchmark assesses whether CLIP models can accurately match these image-text combinations, providing insights into the capabilities and limitations of these models.
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+ ## Dataset Details
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+
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+ - **Content Types:** Text-Image Pairs
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+ - **Volume:** Balanced number of questions for each visual pattern, with each pattern represented by 15 pairs.
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+ - **Source of Data:** Subset from MMVP benchmark, supplemented with additional questions for balance
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+ - **Data Collection Method:** Distillation and categorization of questions from MMVP benchmark into simpler language
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+
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+ ## Usage
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+
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+ ### Intended Use
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+ - Evaluation of CLIP models' ability to understand and process various visual patterns.