2601.13569v2.pdf

{
  "file/base": {
    "record": {
      "extension": ".pdf",
      "hash": "64fb8e667177f8df36042579a930113c60c15187fc886571a4bebfba96cef8f9",
      "media_type": "application/pdf",
      "media_type_prefix": "application",
      "name": "2601.13569v2.pdf",
      "size": 1739297
    },
    "source": {
      "execution_id": "8799fdc6-0be3-4f09-b005-62537d19e032",
      "id": "file/base",
      "type": "Model",
      "version": "1.0.0"
    }
  },
  "file/pdf": {
    "private": false,
    "record": {
      "creation_date": "2026-01-22T01:31:26Z",
      "keywords": [
        "Graph Neural Networks",
        "Digital Watermarking",
        "Information Disentanglement",
        "Reversible Models"
      ],
      "modified_date": "2026-01-22T01:31:26Z",
      "page_count": 12,
      "producer": "pikepdf 8.15.1",
      "title": "DRGW: Learning Disentangled Representations for Robust Graph Watermarking",
      "version": "1.7"
    },
    "source": {
      "execution_id": "9c596b70-574c-4dfb-bc53-f1ef6f8015b8",
      "id": "dorsal/pdf",
      "type": "Model",
      "version": "1.1.0"
    }
  }
}