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/augmask-training-diffusion-models-on-incomplete-tabular-data-via-stochastic-augmentation-and-masking
Subject: AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking
Verdict
Watch
Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.
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": 33, "author": "Jungkyu Kim; Taeyoung Park; Kibok Lee"
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": 33, "author": "Jungkyu Kim; Taeyoung Park; Kibok Lee", "title": "AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking", "creation date": null, "modification date": null, "kids": []}
Inference
{"file name": "input.pdf", "number of pages": 33, "author": "Jungkyu Kim; Taeyoung Park; Kibok Lee", "title": "AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking", "creation date": null, "modification date": null, "kids": []}
Hardware
{"file name": "input.pdf", "number of pages": 33, "author": "Jungkyu Kim; Taeyoung Park; Kibok Lee", "title": "AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking", "creation date": null, "modification date": null, "kids": []}
Receipt path
/buildability/augmask-training-diffusion-models-on-incomplete-tabular-data-via-stochastic-augmentation-and-masking
Paper ref
augmask-training-diffusion-models-on-incomplete-tabular-data-via-stochastic-augmentation-and-masking
arXiv id
2606.03347
Generated at
2026-06-03T20:43:07.135Z
Evidence freshness
fresh
Last verification
2026-06-03T20:43:07.135Z
Sources
3
References
0
Coverage
50%
Lineage hash
ffddeb76bd544a3b62f9cb8e5f0cec474f09d57f37b70e6dbef6ad265954468c
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