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  "access_rights": "",
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  "access_rights": "",
            
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  "author": "A. Radford",
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  "author": "A. Radford",
            
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  "author_email": "",
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  "author_email": "",
            
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  "citation": [
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  "citation": [
            
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    "https://doi.org/10.1109/ICCV51070.2023.01403",
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    "https://doi.org/10.1109/ICCV51070.2023.01403",
            
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    "https://doi.org/10.48550/arXiv.2312.06716",
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    "https://doi.org/10.48550/arXiv.2312.06716",
            
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    "https://doi.org/10.48550/arXiv.2305.05095"
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    "https://doi.org/10.48550/arXiv.2305.05095"
            
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  ],
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  ],
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "defined_in": "https://doi.org/10.48550/arXiv.2306.00301",
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  "defined_in": "https://doi.org/10.48550/arXiv.2306.00301",
            
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  "doi": "10.57702/mxw4bsuu",
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  "doi": "10.57702/mxw4bsuu",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-02",
            
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  "doi_publisher": "TIB",
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  "domain": "https://service.tib.eu/ldmservice",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "J. W. Kim",
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      "extra_author": "J. W. Kim",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "C. Hallacy",
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      "extra_author": "C. Hallacy",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "A. Ramesh",
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      "extra_author": "A. Ramesh",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "G. Goh",
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      "extra_author": "G. Goh",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "S. Agarwal",
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      "extra_author": "S. Agarwal",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "G. Sastry",
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      "extra_author": "G. Sastry",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "A. Askell",
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      "extra_author": "A. Askell",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "P. Mishkin",
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      "extra_author": "P. Mishkin",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "J. Clark",
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      "extra_author": "J. Clark",
            
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      "orcid": ""
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      "orcid": ""
            
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    }
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    }
            
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  ],
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      "name": "computer-vision",
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      "name": "generative-models",
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      "name": "image-segmentation",
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      "name": "image-segmentation",
            
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      "name": "image-synthesis",
            
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      "name": "image-text-pre-training",
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      "title": "Image-Text Pre-training"
            
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      "name": "instance-segmentation",
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      "name": "natural-language-processing",
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      "name": "natural-language-processing",
            
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      "title": "Natural Language Processing"
            
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      "description": "",
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      "name": "text-driven-image-generation",
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      "name": "text-driven-image-generation",
            
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      "title": "Text-Driven Image Generation"
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      "title": "Text-Driven Image Generation"
            
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    },
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      "description": "",
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      "name": "vision-foundation-model",
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      "title": "Vision Foundation Model"
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      "title": "Vision Foundation Model"
            
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      "description": "",
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      "name": "vision-and-language-models",
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      "name": "vision-and-language-models",
            
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      "title": "Vision-and-Language Models"
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      "title": "Vision-and-Language Models"
            
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      "description": "",
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      "name": "visual-representation-learning",
            
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      "title": "Visual Representation Learning"
            
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  "notes": "The CLIP model and its variants are becoming the de facto 
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  "notes": "The CLIP model and its variants are becoming the de facto 
            
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backbone in many applications. However, training a CLIP model from 
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backbone in many applications. However, training a CLIP model from 
            
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hundreds of millions of image-text pairs can be prohibitively 
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hundreds of millions of image-text pairs can be prohibitively 
            
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expensive.",
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expensive.",
            
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      "id": "b5ca1899-21f6-4744-b974-a72e6c60b3bb",
            
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  "type": "dataset",
            
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  "version": ""
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  "version": ""
            
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}
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}