Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
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Page Freshness
Canonical route: /signal-canvas/internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generation
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generation | Route /signal-canvas/internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generation
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generationMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generation",
"query_text": "Summarize Internalizing Geometric Law: Learning from Solver Residuals for Precision-Critical Generation"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "Internalizing Geometric Law: Learning from Solver Residuals for Precision-Critical Generation",
"normalized_query": "2606.09278",
"route": "/signal-canvas/internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generation",
"paper_ref": "internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generation",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: Internalizing Geometric Law: Learning from Solver Residuals for Precision-Critical Generation
PDF: https://arxiv.org/pdf/2606.09278v1
Repository: https://github.com/Huawei-AI4Math/PyGeoX
Source count: 4
Coverage: 67%
Last proof check: 2026-06-09T03:25:41.269Z
Signal Canvas receipt window
/buildability/internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generation
Subject: Internalizing Geometric Law: Learning from Solver Residuals for Precision-Critical Generation
Verdict
Preparing verified analysis
Dimensions overall score 0.0
{"file name": "input.pdf", "number of pages": 24, "author": "Rafael Cabral; Pang Zixi; Ziyi Shou; Shen Xin", "title": "Internalizing Geometric Law: Learning from Solver Residuals for Precision-Critical Generation"
Implication not extracted yet.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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Ignore
Verdict is Ignore because current viability and proof state do not clear the buildability gate.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Receipt path
/buildability/internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generation
Paper ref
internalizing-geometric-law-learning-from-solver-residuals-for-precision-critical-generation
arXiv id
2606.09278
Generated at
2026-06-09T03:25:41.269Z
Evidence freshness
fresh
Last verification
2026-06-09T03:25:41.269Z
Sources
4
References
0
Coverage
67%
Lineage hash
bfacb5c9b14c0f62c4d7a5796bc3f567b6546520ddc4c148a5df10f8a3eab8c9
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Pending verification refs / 4 sources / Verification pending
references
proof_status