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  "access_rights": "",
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  "author": "Rabeeh Karimi Mahabadi",
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  "author": "Rabeeh Karimi Mahabadi",
            
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  "doi": "10.57702/bvpixosy",
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  "doi": "10.57702/bvpixosy",
            
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  "doi_date_published": "2024-12-03",
            
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  "extra_authors": [
            
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    {
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      "extra_author": "James Henderson",
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      "extra_author": "James Henderson",
            
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      "orcid": ""
            
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    },
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    {
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    {
            
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      "extra_author": "Iz Beltagy",
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      "extra_author": "Iz Beltagy",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Hamish Ivison",
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      "extra_author": "Hamish Ivison",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Matthew E. Peters",
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      "extra_author": "Matthew E. Peters",
            
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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": "Jaesung Tae",
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      "extra_author": "Jaesung Tae",
            
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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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      "extra_author": "Arman Cohan",
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      "extra_author": "Arman Cohan",
            
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      "orcid": ""
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      "orcid": ""
            
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    }
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      "name": "natural-language-processing",
            
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      "title": "Natural Language Processing"
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      "title": "Natural Language Processing"
            
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      "name": "text-generation",
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      "name": "text-generation",
            
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      "title": "Text Generation"
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      "title": "Text Generation"
            
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  "metadata_modified": "2024-12-03T09:34:06.016871",
            
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  "name": "tess--text-to-text-self-conditioned-simplex-diffusion",
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  "name": "tess--text-to-text-self-conditioned-simplex-diffusion",
            
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  "notes": "Diffusion models have emerged as a power-ful paradigm for 
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  "notes": "Diffusion models have emerged as a power-ful paradigm for 
            
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generation, obtaining strong performance in various continuous 
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generation, obtaining strong performance in various continuous 
            
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domains. However, applying continuous diffusion models to natural 
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domains. However, applying continuous diffusion models to natural 
            
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language remains challenging due to its discrete nature and the need 
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language remains challenging due to its discrete nature and the need 
            
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for a large number of diffusion steps to generate text, making 
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for a large number of diffusion steps to generate text, making 
            
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diffusion-based generation expensive.",
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diffusion-based generation expensive.",
            
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      "name": "natural language processing",
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      "id": "064311a6-1694-4cd5-9b57-9a33271b140e",
            
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      "name": "text generation",
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      "name": "text generation",
            
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    }
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  ],
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  "title": "TESS: Text-to-Text Self-Conditioned Simplex Diffusion",
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  "title": "TESS: Text-to-Text Self-Conditioned Simplex Diffusion",
            
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  "type": "dataset",
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  "version": ""
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  "version": ""
            
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}
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}