[
  {
    "Accuracy": 88.5,
    "code_links": [
      {
        "title": "Tiiiger/SGC",
        "url": "https://github.com/Tiiiger/SGC"
      },
      {
        "title": "marblet/GNN_models_pytorch_geometric",
        "url": "https://github.com/marblet/GNN_models_pytorch_geometric"
      },
      {
        "title": "reallygooday/60daysofudacity",
        "url": "https://github.com/reallygooday/60daysofudacity"
      },
      {
        "title": "cvignac/gnn_statistics",
        "url": "https://github.com/cvignac/gnn_statistics"
      },
      {
        "title": "snisher/Cora-Graph-Learning",
        "url": "https://github.com/snisher/Cora-Graph-Learning"
      }
    ],
    "date": "2019-02-19",
    "date2": 20190219,
    "model": "SGC",
    "paper": {
      "title": "Simplifying Graph Convolutional Networks",
      "url": "https://cknow.io/lib/111ae59d4e2ab614"
    },
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        "title": "Tiiiger/SGC",
        "url": "https://github.com/Tiiiger/SGC"
      },
      {
        "title": "marblet/GNN_models_pytorch_geometric",
        "url": "https://github.com/marblet/GNN_models_pytorch_geometric"
      },
      {
        "title": "reallygooday/60daysofudacity",
        "url": "https://github.com/reallygooday/60daysofudacity"
      },
      {
        "title": "cvignac/gnn_statistics",
        "url": "https://github.com/cvignac/gnn_statistics"
      },
      {
        "title": "snisher/Cora-Graph-Learning",
        "url": "https://github.com/snisher/Cora-Graph-Learning"
      }
    ],
    "date": "2019-02-19",
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    "model": "SGCN",
    "paper": {
      "title": "Simplifying Graph Convolutional Networks",
      "url": "https://cknow.io/lib/111ae59d4e2ab614"
    },
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  },
  {
    "Accuracy": 86.34,
    "code_links": [
      {
        "title": "plkmo/Bible_Text_GCN",
        "url": "https://github.com/plkmo/Bible_Text_GCN"
      },
      {
        "title": "koreyou/text-gcn-chainer",
        "url": "https://github.com/koreyou/text-gcn-chainer"
      },
      {
        "title": "codeKgu/text-gcn",
        "url": "https://github.com/codeKgu/text-gcn"
      },
      {
        "title": "yongbowin/Bible_Text_GCN_annotation",
        "url": "https://github.com/yongbowin/Bible_Text_GCN_annotation"
      }
    ],
    "date": "2018-09-15",
    "date2": 20180915,
    "model": "Text GCN",
    "paper": {
      "title": "Graph Convolutional Networks for Text Classification",
      "url": "https://cknow.io/lib/57ddd1e4784814b7"
    },
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  {
    "Accuracy": 86.19,
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    "Precision": 86.2,
    "Recall": 86.18,
    "code_links": [
      {
        "title": "vgupta123/SCDV-MS",
        "url": "https://github.com/vgupta123/SCDV-MS"
      }
    ],
    "date": "2019-11-18",
    "date2": 20191118,
    "model": "SCDV-MS",
    "paper": {
      "title": "Improving Document Classification with Multi-Sense Embeddings",
      "url": "https://cknow.io/lib/478aaa79b868aa2c"
    },
    "paper_data_uoa": "478aaa79b868aa2c"
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  {
    "Accuracy": 74.78,
    "code_links": [
      {
        "title": "matwerner/fast-wmd",
        "url": "https://github.com/matwerner/fast-wmd"
      }
    ],
    "date": "2019-12-01",
    "date2": 20191201,
    "model": "REL-RWMD k-NN",
    "paper": {
      "title": "Speeding up Word Mover's Distance and its variants via properties of distances between embeddings",
      "url": "https://cknow.io/lib/cc93cc27e45d6bd6"
    },
    "paper_data_uoa": "cc93cc27e45d6bd6"
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]