2601.06224v2.pdf

{
  "dorsal/arxiv": [
    {
      "date_modified": "2026-02-17T05:53:07.509000Z",
      "hash": "58736ec8cd326af82bdba15b32896da27a02eeea28d65d4608bd66e0ce42c02c",
      "id": "320dac54-324b-4e56-ac8c-360ce857033a",
      "source": {
        "execution_id": "b873a1e3-2468-4e56-bff9-5c679d1346ff",
        "id": "arXiv Dataset",
        "type": "Model",
        "variant": "snapshot-2026-01-17",
        "version": "0.1.0"
      },
      "user_id": 1000002
    }
  ],
  "file/base": {
    "record": {
      "extension": ".pdf",
      "hash": "58736ec8cd326af82bdba15b32896da27a02eeea28d65d4608bd66e0ce42c02c",
      "media_type": "application/pdf",
      "media_type_prefix": "application",
      "name": "2601.06224v2.pdf",
      "size": 1813285
    },
    "source": {
      "execution_id": "a14d90b1-9486-4232-b6af-deafa00e466a",
      "id": "file/base",
      "type": "Model",
      "version": "1.0.0"
    }
  },
  "file/pdf": {
    "private": false,
    "record": {
      "keywords": [],
      "page_count": 9,
      "producer": "pikepdf 8.15.1",
      "title": "Ground What You See: Hallucination-Resistant MLLMs via Caption Feedback, Diversity-Aware Sampling, and Conflict Regularization",
      "version": "1.7"
    },
    "source": {
      "execution_id": "bf687ed6-874f-42be-bbf9-da4b43103807",
      "id": "dorsal/pdf",
      "type": "Model",
      "version": "1.1.0"
    }
  }
}