{
  "schema_version": "1.0",
  "id": "s13:https://arxiv.org/abs/2607.12982v1",
  "slug": "2607-12982v1-1f3ilxi",
  "url": "https://feed7.dev/p/2607-12982v1-1f3ilxi",
  "title": "FormalAnalyticGeo: A Neural-Symbolic Based Framework for Multimodal Analytic Geometry Problem Generation",
  "why_included": "FormalAnalyticGeo shows a reusable synthetic-data pipeline: agents generate problems, compile them into a formal representation, render exact diagrams, measure answers, and retry failed checks.",
  "summary": "FormalAnalyticGeo chains **four specialized LLM components** around CDL, a formal intermediate representation rendered by an SDF engine. The pipeline produced **over 7K verified problems** with aligned text, diagrams, annotations, and answers.",
  "practical_implication": "For synthetic multimodal data, insert a machine-checkable representation between generation and rendering, then use staged verification and retries. This separates creative problem generation from geometric precision and answer extraction.",
  "agent_context": "FormalAnalyticGeo chains **four specialized LLM components** around CDL, a formal intermediate representation rendered by an SDF engine. The pipeline produced **over 7K verified problems** with aligned text, diagrams, annotations, and answers.\n\nFor synthetic multimodal data, insert a machine-checkable representation between generation and rendering, then use staged verification and retries. This separates creative problem generation from geometric precision and answer extraction.\n\nReported outputs had **0.70% median relative error**, with **82.3% within 5%** of exact symbolic answers. The material says the framework and dataset will be released, so availability and performance beyond analytic geometry remain open.",
  "source": {
    "name": "arXiv",
    "url": "https://arxiv.org/abs/2607.12982v1",
    "published_at": "2026-07-14T17:24:57.000Z"
  },
  "source_class": "blog_post",
  "content_type": "Paper",
  "layer": "agent",
  "domains": [
    "research",
    "data"
  ],
  "topics": [
    "multi-agent",
    "harness-engineering"
  ],
  "verification": {
    "status": "needs_review",
    "label": "Needs Review",
    "method": "unverified",
    "verified_at": null
  },
  "uncertainty": [
    "Reported outputs had **0.70% median relative error**, with **82.3% within 5%** of exact symbolic answers. The material says the framework and dataset will be released, so availability and performance beyond analytic geometry remain open."
  ],
  "lifecycle": "Current",
  "published_at": "2026-07-14T17:24:57.000Z",
  "modified_at": "2026-07-14T17:24:57.000Z",
  "supersedes": [],
  "expires_at": null,
  "formats": {
    "html": "https://feed7.dev/p/2607-12982v1-1f3ilxi",
    "json": "https://feed7.dev/p/2607-12982v1-1f3ilxi.json",
    "markdown": "https://feed7.dev/p/2607-12982v1-1f3ilxi.md"
  }
}