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  "author": "Christoph Schuhmann",
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  "author": "Bingchen Zhao",
            
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  "defined_in": "https://doi.org/10.48550/arXiv.2301.07088",
            
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  "doi": "10.57702/t5pv0rdq",
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  "doi": "10.57702/t5pv0rdq",
            
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  "doi_date_published": "2024-12-03",
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  "doi_date_published": "2024-12-03",
            
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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": "Richard Vencu",
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      "extra_author": "Quan Cui",
            
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    },
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    {
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      "extra_author": "Romain Beaumont",
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      "extra_author": "Hao Wu",
            
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    },
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    {
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      "extra_author": "Robert Kaczmarczyk",
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      "extra_author": "Osamu Yoshie",
            
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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": "Clayton Mullis",
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      "extra_author": "Cheng Yang",
            
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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": "Aarush Katta",
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      "extra_author": "Oisin Mac Aodha",
            
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      "orcid": ""

            
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    },

            
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      "extra_author": "Theo Coombes",

            
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      "extra_author": "Jenia Jitsev",

            
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    },

            
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      "extra_author": "Aran Komatsuzaki",

            
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      "description": "",
            
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  "landing_page": "https://arxiv.org/abs/2106.10265",
            
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  "name": "laion400m",
            
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  "notes": "Laion400M is a large-scale dataset for visual 
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  "notes": "The dataset used in this paper is a large-scale web 
            
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