Opportunities/Formal Mathematics Benchmarking

A possibility worth exploring

Formal Mathematics Benchmarking

Evaluate proof agents on source-linked research statements, known partial results, false-proof traps and machine-checkable subgoals.

01

The possibility

Evaluate proof agents on source-linked research statements, known partial results, false-proof traps and machine-checkable subgoals.

Research-level benchmarks can measure whether AI systems formalize, retrieve, decompose and verify mathematics rather than merely produce plausible prose.

A living benchmark can absorb newly formalized results and later test reconstruction of genuine breakthroughs.

02

What to keep in mind

What stands between here and there?

Known limitation

Agents can overfit benchmarks or succeed on formal syntax without generating meaningful new mathematics.

Honest boundary

Benchmark scores must not be described as proof progress on the underlying open problem.

03

Ideas it sparks

Ways to start thinking today.

These are prompts for curiosity—not roadmaps or promises.

Strongly supported

Formal Proof-Agent Benchmark

A graded benchmark of formal statements, known lemmas, finite certificates, dependency retrieval and adversarial false-proof traps.

Why it is thinkable now

Yes, using existing Lean repositories and source-backed partial results.

Explore the idea →
Sources and uncertainty 4

AI summarized and source-backed · Qualified expert review pending.