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Lean proof verification

Lean Proof Verification vs Mathematical Peer Review

Lean proof verification checks a formal proposition within a declared trust base. Mathematical peer review evaluates a broader scholarly submission. They overlap, but neither should be described as a substitute for the other.

Published Haivian Technology · AI-assisted editorial review
Two distinct review pathways for formal proof checking and scholarly peer review
Lean proof verification checks a formal proposition within a declared trust base. Mathematical peer review evaluates a broader scholarly submission. They overlap, but neither should be described as a substitute for the other.

Two processes that answer different questions

Lean proof verification asks whether an encoded proposition follows within a formal environment and trust base. Mathematical peer review asks experts to critically assess a submitted work for an editorial venue. Peer review may consider significance, exposition, originality and mathematical reasoning, but its exact process varies; it should not be assumed to include code execution, axiom inspection or kernel replay.

ProcessMain questionTypical evidenceBoundary
Lean kernel checkingDoes this proof term have the claimed formal type?Source, declarations, imports, proof term and kernel acceptanceDoes not establish that the type matches the paper’s intended claim.
Independent Lean artifact auditCan the exact target be rebuilt, inspected and replayed, and what does it correspond to?Frozen versions, build logs, theorem identity, axiom closure, replay and correspondence analysisLimited to accepted scope, artifacts and checks actually performed.
Mathematical peer reviewShould this submission be accepted, revised or rejected under a venue’s standards?Expert reading, referee reports, author revisions and editorial judgmentProcess varies and does not automatically include formal or computational verification.

Where they overlap

Both can challenge definitions, assumptions and conclusions. A careful referee may find a formalization mismatch; a formal audit may identify an unsupported informal consequence. Neither label tells you which checks actually occurred. The record must do that.

When to commission both

Use both when a central theorem has a formal artifact and the broader paper also depends on novelty, mathematical interpretation, exposition or consequences outside that artifact. Formal verification can provide unusually precise evidence for a target; peer review can assess the larger scholarly contribution. The two records should cross-reference the same version and preserve disagreements.

Sources and further reading

Authorship and relationship disclosure

Original article author and publisher: Haivian Technology, a brand of Qonduit Limited, New Zealand. This is AI-assisted company editorial work. Haivian sells research-audit services and publishes the Validation Journal under common organizational control. “Third-party” describes Haivian’s relationship to a research producer only where Haivian did not produce the audited research; it does not mean external journal peer review, institutional accreditation or independent human-expert certification.

Scope, source versions and trust assumptions determine every finding. An optional audit-to-publication pathway is separately assessed and does not guarantee publication or a favourable result.