Buildability / Receipt
This public receipt window renders only fields present in the canonical receipt object, deterministic fixture receipt, or canonical evidence receipt. Missing compute, demo, hash, signature, approval, telemetry, and adoption fields stay explicit.
Public buildability page receipt window
/buildability/learning-geometric-representations-from-videos-for-spatial-intelligent-multimodal-large-language-models
Subject: Learning Geometric Representations from Videos for Spatial Intelligent Multimodal Large Language Models
Verdict
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.
Data
{"file name": "input.pdf", "number of pages": 11, "author": "Haibo Wang; Lifu Huang"
Truth Boundary
Buildability surfaces only report computed viability and proof receipts. They do not claim live production usage, pilot outcomes, founder sign-off, public Brier calibration, judge divergence, or external adoption unless explicitly sourced.
Compute
{"file name": "input.pdf", "number of pages": 11, "author": "Haibo Wang; Lifu Huang", "title": "Learning Geometric Representations from Videos for Spatial Intelligent Multimodal Large Language Models", "creation date": null, "modification date": null, "kids": []}
Inference
{"file name": "input.pdf", "number of pages": 11, "author": "Haibo Wang; Lifu Huang", "title": "Learning Geometric Representations from Videos for Spatial Intelligent Multimodal Large Language Models", "creation date": null, "modification date": null, "kids": []}
Hardware
{"file name": "input.pdf", "number of pages": 11, "author": "Haibo Wang; Lifu Huang", "title": "Learning Geometric Representations from Videos for Spatial Intelligent Multimodal Large Language Models", "creation date": null, "modification date": null, "kids": []}
Receipt path
/buildability/learning-geometric-representations-from-videos-for-spatial-intelligent-multimodal-large-language-models
Paper ref
learning-geometric-representations-from-videos-for-spatial-intelligent-multimodal-large-language-models
arXiv id
2606.05833
Generated at
2026-06-06T03:20:52.336Z
Evidence freshness
fresh
Last verification
2026-06-06T03:20:52.336Z
Sources
3
References
0
Coverage
50%
Lineage hash
4314cb5c28fda8c12dd601d88cac8ebe3662ff782ed36c1302583ac3f7703df9
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.
Canonical opportunity-kernel evidence is available for this receipt window.
repo_url
references