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  "author": "Yulin Pan",
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  "doi": "10.57702/9jkxnjlo",
            
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  "doi_date_published": "2025-01-03",
            
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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": "Xiangteng He",
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      "extra_author": "Xiangteng He",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Biao Gong",
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      "extra_author": "Biao Gong",
            
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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": "Yiliang Lv",
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      "extra_author": "Yiliang Lv",
            
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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": "Yujun Shen",
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      "extra_author": "Yujun Shen",
            
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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": "Yuxin Peng",
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      "extra_author": "Yuxin Peng",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Deli Zhao",
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      "extra_author": "Deli Zhao",
            
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      "orcid": ""
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      "orcid": ""
            
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      "description": "",
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      "description": "",
            
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      "name": "video-grounding",
            
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  "metadata_modified": "2025-01-03T01:12:52.857427",
            
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  "name": 
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  "name": 
            
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"mad--a-large-scale-benchmark-for-long-form-video-temporal-grounding",
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"mad--a-large-scale-benchmark-for-long-form-video-temporal-grounding",
            
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  "notes": "MAD: A large-scale benchmark for long-form video temporal 
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  "notes": "MAD: A large-scale benchmark for long-form video temporal 
            
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grounding, containing over 384K natural language queries that derived 
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grounding, containing over 384K natural language queries that derived 
            
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from high-quality audio description of mainstream movies and grounded 
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from high-quality audio description of mainstream movies and grounded 
            
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in over 1.2K hours of videos with very low coverage.",
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in over 1.2K hours of videos with very low coverage.",
            
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      "id": "9a2e391b-7e48-4bba-a4d1-abece2a01902",
            
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      "name": "temporal grounding",
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      "name": "temporal grounding",
            
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      "state": "active",
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      "vocabulary_id": null
            
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    }
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    }
            
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  ],
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  ],
            
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  "title": "MAD: A Large-Scale Benchmark for Long-Form Video Temporal 
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  "title": "MAD: A Large-Scale Benchmark for Long-Form Video Temporal 
            
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Grounding",
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Grounding",
            
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  "type": "dataset",
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  "type": "dataset",
            
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  "version": ""
            
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}
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}