Primary evidence
- Lean-STaR: Learning to Interleave Thinking and ProvingS1 · Primary research · Paper · 2024-07-14
Lean-STaR trains theorem provers to interleave informal thinking with Lean tactics
The method generates retrospective thoughts from known tactics and then uses expert iteration on newly discovered verified proofs.
What happened?
Lean-STaR improved miniF2F pass@64 from 43.4% to 46.3% by training models to generate synthetic informal thoughts before tactics.
Why it matters
It explored a direct bridge between chain-of-thought-style reasoning and proof-assistant feedback.
Significance rationale: Lean-STaR explicitly inserted learned informal thoughts before proof steps and combined them with expert iteration.
Historical context
Earlier developments
Later developments
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Related milestones
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Evidence & status at a glance
- Significance
- H2 · Field milestone
- Verification
- Paper released
- Evidence level
- E2 · Research record
- AI role
- AI primary, human verified
- Formal assurance
- Machine-checked
Contribution & verification
- Mathematical novelty
- Benchmark result
- Interface
- Informal, Formal, Hybrid
- AI contribution
- The model generates both informal thoughts and Lean tactics, while Lean verifies the proof state.
- Human contribution
- Researchers designed synthetic-thought generation, expert iteration and evaluation.
- Verification
- Paper released · E2 · Research record · Machine-checked
- Last reviewed
- 2026-09-11
Technical details
- Systems
- lean-star, lean
- Organizations
- carnegie-mellon-university
- Problems
- minif2f
- Methods
- expert-iteration, synthetic-thought, lean
Sources & artifacts
- Lean-STaR: Learning to Interleave Thinking and ProvingS1 · Primary research · Paper · accessed 2026-09-10
Verification history
- 2024-07-14 · Paper released · E2 · Research record
The Chronicle records this event from the cited primary or official source; the status does not imply independent Chronicle verification.
Corrections
No corrections recorded.