Forging More Tasks into Better Harnesses: Agentic Harness Evolution via Successive Scale Racing

Not provided in the abstract

agentic harnessevolutionary optimizationtask performanceevidence selection

2610.28815

Builder Relevance

80%

2h ago

Abstract

The paper discusses a framework called Successive Scale Racing (SSR) that optimizes agentic harness evolution by adaptively searching for optimal evidence combinations, improving performance as task pools expand.

Reality Card

Core Claim

SSR achieves state-of-the-art results across three benchmarks, improving the pass rate from 64.3% to 68.3% as the task pool grows from 40 to 200.

Method / Result

SSR reduces validation executions by 60% while identifying near-optimal candidates.

Limitations

The paper does not specify the authors or provide detailed reproducibility metrics.

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