{
  "added_at": "2026-10-20",
  "arxiv_id": "2610.20538",
  "arxiv_version_reviewed": "v1",
  "authors": [
    "Qiushi Sun",
    "Jingyang Gong",
    "Yang Liu",
    "Qiaosheng Chen",
    "Zhangyue Yin",
    "Zixian Huang",
    "Hanxu Hu",
    "Jing Xiong",
    "Fangzhi Xu",
    "Haochen Tan",
    "Haoli Bai",
    "Lifeng Shang",
    "Xiaoguang Li",
    "Ben Kao",
    "Qipeng Guo",
    "Lingpeng Kong",
    "Jiahui Gao"
  ],
  "bibtex_url": "https://awesomerea.org/papers/citations/paper-prismacoder.bib",
  "code_url": null,
  "date_basis": "First arXiv submission; no reviewed venue publication is established.",
  "date_basis_zh": "采用首次 arXiv 提交日期；未确立正式期刊或会议出版。",
  "date_precision": "day",
  "description_en": "Trains visual-code models using separate code and rendered-output rubrics for data filtering and reinforcement learning. Relevant evaluations include rebuilding webpages, charts and vector graphics from images.",
  "description_zh": "以代码与渲染结果的独立评分准则筛选数据并训练视觉代码模型，相关评测包括根据图像重建网页、图表和矢量图。",
  "doi": "10.48550/arxiv.2610.20538",
  "entry_url": "https://awesomerea.org/papers/paper-prismacoder/",
  "entry_url_zh": "https://awesomerea.org/zh/papers/paper-prismacoder/",
  "evidence_urls": [
    "https://arxiv.org/abs/2610.20538v1",
    "https://arxiv.org/html/2610.20538v1",
    "https://api.datacite.org/dois/10.48550/arxiv.2610.20538",
    "https://qiushisun.github.io/PrismaCoder-Home/",
    "https://huggingface.co/collections/QiushiSun/prismacoder",
    "https://huggingface.co/QiushiSun/PrismaCoder-9B/tree/d5743a565f9f9b55da0798c4636059074f21602a",
    "https://huggingface.co/QiushiSun/PrismaCoder-35B-A3B-SFT/tree/e2df1e846cbfe5a2aebc860917b02c742007c62e"
  ],
  "first_arxiv_date": "2026-10-14",
  "id": "paper-prismacoder",
  "json_url": "https://awesomerea.org/papers/paper-prismacoder/record.json",
  "kind": "research",
  "markdown_url": "https://awesomerea.org/papers/paper-prismacoder/index.md",
  "markdown_url_zh": "https://awesomerea.org/zh/papers/paper-prismacoder/index.md",
  "metadata_notes": "Work in progress. DataCite confirms the DOI despite the arXiv pending label. The project code link is pending; the dataset API returned HTTP 401 anonymously. Reviewed model inventories include 9B and 35B-A3B-SFT with MIT card metadata.",
  "metadata_notes_zh": "仍在进行中的工作。DataCite 已确认 DOI，arXiv 的待注册标记未同步。项目代码链接待发布，匿名数据集 API 返回 HTTP 401。已查模型文件清单包括 9B、35B-A3B-SFT，模型卡声明 MIT。",
  "pdf_url": "https://arxiv.org/pdf/2610.20538v1",
  "project_url": "https://qiushisun.github.io/PrismaCoder-Home/",
  "publication_date": "2026-10-14",
  "publication_status": "preprint",
  "record_type": "paper",
  "runtime_tested": false,
  "scope_limitations_en": "Combines visual reconstruction with text-driven generation. Judge scores do not establish behavioral equivalence. Training and evaluation share some judge families; the human check uses 100 samples. Instruction n-gram filtering cannot exclude all pretraining exposure.",
  "scope_limitations_zh": "同时涵盖视觉重建与文本生成，裁判评分不证明行为等价。训练与评测部分共用裁判模型家族，人工检查使用 100 个样本；指令 n-gram 过滤不能排除所有预训练接触。",
  "targets": [
    "website",
    "app"
  ],
  "title": "PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis",
  "title_zh": "PrismaCoder：通过分解式评分准则生成提升开放多模态代码能力",
  "url": "https://arxiv.org/abs/2610.20538",
  "venue": "arXiv",
  "verification": "source-reviewed",
  "verified_at": "2026-10-20",
  "why_fits_en": "Provides a recent approach to reconstruction from rendered evidence.",
  "why_fits_zh": "补充依据渲染结果进行重建的近期方法。",
  "year": 2026
}