{
  "schema_version": 2,
  "id": "2603.14609",
  "source_urls": [
    "https://arxiv.org/html/2603.14609v1"
  ],
  "source_kind": "official_arxiv_html_or_abs",
  "capture_window_utc": {
    "start": "2026-10-20T18:48:00Z",
    "end": "2026-10-20T18:56:04Z"
  },
  "original_capture_sha256": "615263cb567a68ee2fdd256d05e8e729fb926e0c70f12832580962069929d790",
  "original_capture_hash_scope": "complete original UTF-8 browser excerpt receipt archived only in local private temporary storage; not the original HTTP response body",
  "public_receipt_kind": "source_metadata_locations_and_chinese_paraphrase_without_verbatim_article_or_internal_browser_references",
  "source_locations": {
    "read_sections": [
      "§3数据构建",
      "§4.2-4.3"
    ],
    "browser_line_ranges": "L93;L221-L238"
  },
  "full_article_read": false,
  "method_paraphrase_zh": "GroundSet将地籍vector对象与航空影像对齐，自动生成spatial理解任务；vanilla VLM LoRA作为数据贡献baseline，无额外空间网络。",
  "experiment_paraphrase_zh": "85,864km²/20行政区、20cm影像；多VLM在caption/VQA/classification/detection/REC/segmentation上比较；1 epoch LoRA用8×A100约72h。"
}