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/llm-attribution-analysis-across-different-fine-tuning-strategies-and-model-scales-for-automated-code-compliance
Subject: LLM attribution analysis across different fine-tuning strategies and model scales for automated code compliance
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
LLM attribution analysis across different fine-tuning strategies and model scales for automated code compliance Jack Wei Lun Shi1, Minghao Dang1,2, Wawan Solihin1,3, Justin K.W
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
LLM attribution analysis across different fine-tuning strategies and model scales for automated code compliance Jack Wei Lun Shi1, Minghao Dang1,2, Wawan Solihin1,3, Justin K.W. Yeoh1 1 Department of Civil and Environmental Engineering, National University of Singapore, 117576
Inference
LLM attribution analysis across different fine-tuning strategies and model scales for automated code compliance Jack Wei Lun Shi1, Minghao Dang1,2, Wawan Solihin1,3, Justin K.W. Yeoh1 1 Department of Civil and Environmental Engineering, National University of Singapore, 117576
Hardware
LLM attribution analysis across different fine-tuning strategies and model scales for automated code compliance Jack Wei Lun Shi1, Minghao Dang1,2, Wawan Solihin1,3, Justin K.W. Yeoh1 1 Department of Civil and Environmental Engineering, National University of Singapore, 117576
Receipt path
/buildability/llm-attribution-analysis-across-different-fine-tuning-strategies-and-model-scales-for-automated-code-compliance
Paper ref
llm-attribution-analysis-across-different-fine-tuning-strategies-and-model-scales-for-automated-code-compliance
arXiv id
2604.15589
Generated at
2026-04-20T20:24:39.818Z
Evidence freshness
stale
Last verification
2026-04-20T20:24:39.818Z
Sources
3
References
0
Coverage
50%
Lineage hash
8b3275d14bdbd3b352e8ee9aca968d28c229af50b12a8e90247722782eadba8a
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.
Some score or evidence fields are outside the preferred freshness window.
repo_url
references