AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses
Recent work on distillation transfers the capabilities of large models to smaller ones often by updating the latter's parameters, through teacher forcing, on-policy distillation, and related training-time methods. In this paper, we ask whether such transfer can instead occur at test time. We study strong-to-weak scaffolding: whether a stronger builder model can construct inference-time harnesses that help a weaker target model solve tasks more reliably without any parameter updates. Using four r
Record details
Published: 12 August 2026
Source: arXiv cs.AI
Category: Research
Topics: Regulation
Retrieved: 13 August 2026
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How to cite this record
ethics.ai (12 August 2026), “AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses,” evidence record 19019, https://ethics.ai/record/19019 (originally published by arXiv cs.AI).
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