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Harness-Zero: Harness Distillation via Agent-as-Harness

Research LLM Agents

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TL;DR - Harness-Zero distills behaviors induced by specialized agent harnesses into model weights, allowing agents to retain performance gains while deploying with one fixed harness. It nearly doubles macro-average task success from 23.3% to 44.3%, surpassing the 41.7% achieved with the specialized harness attached.

  • A harnessing agent translates optimized-harness guidance into corrected demonstrations compatible with the target harness’s action space.
  • Fine-tuning on these trajectories internalizes specialized tool-use and reasoning behaviors, removing the need for deployment-time harness routing.
  • Across knowledge work, tool use, and science tasks, agent-as-harness outperformed code-as-harness for frontier LLMs using the same evolved harness.
  • The method recovered 82.3% on average of 28 harness-induced behavioral patterns absent from the base model.

Sources (1)

Harness-Zero: Harness Distillation via Agent-as-Harness

arXiv cs.AI Haoran Ye, Yuxing Lu, Haonan Dong, Zhaochen Su, Guojie Song 2026-09-21 arXiv:2609.24974
Public signals Hugging Face upvotes 35
Providers: Hugging Face · Upvotes 35 OpenAlex · N/A Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-25 14:17:07.184407 UTC

TL;DR - Harness-Zero distills behaviors induced by specialized agent harnesses into model weights, allowing agents to retain performance gains while deploying with one fixed harness. It nearly doubles macro-average task success from 23.3% to 44.3%, surpassing the 41.7% achieved with the specialized harness attached.

  • A harnessing agent translates optimized-harness guidance into corrected demonstrations compatible with the target harness’s action space.
  • Fine-tuning on these trajectories internalizes specialized tool-use and reasoning behaviors, removing the need for deployment-time harness routing.
  • Across knowledge work, tool use, and science tasks, agent-as-harness outperformed code-as-harness for frontier LLMs using the same evolved harness.
  • The method recovered 82.3% on average of 28 harness-induced behavioral patterns absent from the base model.
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