{
  "url": "https://appliedfrontier.nl/en/research/signal-5c564b4f4e989395/",
  "title": "Verifiable Geometry Problem Solving: Solver-Driven Autoformalization and Theorem Proposing",
  "published": "2026-06-26",
  "excerpt": "Geometry Problem Solving have increasingly adopt the neuro-symbolic paradigm, combining neural intuition with symbolic rigor. However, current frameworks suffer from severe bottlenecks in two core",
  "content_sha256": "e192c77fc4a0250a112fa201ba1f91102a5e4976be243b7a0e24733df6845963",
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  "artifact_links": [
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  ],
  "arxiv_id": "2606.27926",
  "id": "signal-5c564b4f4e989395",
  "org": "Research community",
  "topic": "Formal verification",
  "source_kind": "preprint",
  "status": "unreviewed-source-report",
  "analysis_method": "deterministic_metadata_triage_v1",
  "novelty_verified": false,
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  "matched_terms": [
    "geometry",
    "theorem"
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  "checked_at": "2026-10-29T22:08:08+00:00",
  "first_seen": "2026-10-29T21:52:00+00:00",
  "source_hash": "92d23edcb7b5b750b328c84f9e41e32485b6dc55227c0d8049ac46dabef730d0",
  "source_url": "https://arxiv.org/abs/2606.27926",
  "language": "en",
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}