Recursive Harness Self-Improvement for Frontier Reasoning Data Synthesis
Quick summary
arXiv:2610.03548v1 Announce Type: new Abstract: Generating progressively harder reasoning problems requires synthesis procedures that adapt as the task distribution evolves. Existing task-level recursion reuses generated problems as seeds but leaves the construction harness unchanged. We present task-harness co-evolution, a framework for recursive harness self-improvement (RSI) in reasoning-data synthesis. Online self-improvement converts intermediate solver failures into reusable skills during generation. Post-task self-improvement revises skills, prompts, and workflows after each batch, adop
Key takeaways
- arXiv:2610.03548v1 Announce Type: new Abstract: Generating progressively harder reasoning problems requires synthesis procedures that adapt as the task distribution evolves.
- Existing task-level recursion reuses generated problems as seeds but leaves the construction harness unchanged.
- We present task-harness co-evolution, a framework for recursive harness self-improvement (RSI) in reasoning-data synthesis.
Why it matters
“Recursive Harness Self-Improvement for Frontier Reasoning Data Synthesis” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.
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