pith:V55XZYK2
When Should an AI Workflow Release? Always-Valid Inference for Black-Box Generate-Verify Systems
A hard-negative reference pool of high-scoring failures gives finite-sample control over when black-box AI workflows release outputs on infeasible tasks.
arxiv:2605.12947 v1 · 2026-05-13 · stat.ML · cs.AI · cs.LG · stat.ME
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\pithnumber{V55XZYK2HASK3NDXNHQME2X2WL}
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Claims
a conservative reference pool yields finite-sample control of the probability of releasing on infeasible tasks, that is, tasks for which the given workflow is not capable of producing a reliable solution.
That a hard-negative reference pool of high-scoring failures can be built that is sufficiently conservative to deliver finite-sample error control yet not so conservative that it blocks release on feasible tasks where moderate evidence accumulates.
A wrapper for black-box generate-verify AI pipelines that uses a conservative hard-negative reference pool and e-processes to control the probability of releasing on infeasible tasks while permitting release on feasible ones.
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| First computed | 2026-05-18T03:09:09.473696Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/V55XZYK2HASK3NDXNHQME2X2WL \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: af7b7ce15a3824adb47769e0c26afab2c733a8de9b0611a9b3cbb09193eb8ff5
Canonical record JSON
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