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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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# MMVP-VLM Benchmark Datacard |
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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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- **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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## Usage |
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### Intended Use |
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- Evaluation of CLIP models' ability to understand and process various visual patterns. |
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