#harness-optimization News & Analysis

2 articles tagged with #harness-optimization. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Jun 57/10

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Retrospective Harness Optimization: Improving LLM Agents via Self-Preference over Trajectory Rollouts

Researchers introduce Retrospective Harness Optimization (RHO), a self-supervised method that enables AI agents to improve their capabilities using only historical trajectory data without requiring external validation sets. The approach improved performance on SWE-Bench Pro from 59% to 78% pass rate in a single optimization round, demonstrating practical effectiveness across software engineering, technical work, and knowledge domains.

AINeutralarXiv – CS AI · May 276/10

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It's Not the Capability: Harness Sensitivity Is Non-Monotone Across LLM Agent Tiers

A controlled study of 432 experiments across six LLM models challenges the assumption that higher-capability models require less structural guidance. The research reveals non-monotone harness sensitivity patterns, where frontier models like Gemini 2.5 Flash show performance degradation with increased harness complexity, while reasoning-focused models benefit from stricter constraints.

🧠 Gemini