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VQV Signal

RESEARCH SOURCE-BACKED TECHNICAL

HarnessPro: Recursive Harness Self-Improvement with Pareto Optimization for Performance-Cost Trade-offs

Harness development plays a crucial role in building capable AI agents. Recent approaches improve harnesses through recursive self-improvement (RSI), but their performance gains often come with higher execution costs. We introduce HarnessPro, a label-free met...

Source: arXiv · arxiv.org Published 2026-10-19T17:27:38+00:00 Detected 2026-10-20T09:17:54+00:00
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Harness development plays a crucial role in building capable AI agents. Recent approaches improve harnesses through recursive self-improvement (RSI), but their performance gains often come with higher execution costs. We introduce HarnessPro, a label-free met...

Harness development plays a crucial role in building capable AI agents. Recent approaches improve harnesses through recursive self-improvement (RSI), but their performance gains often come with higher execution costs. We introduce HarnessPro, a label-free method for evolving harnesses to improve task performance...

Signal Strength 95% Technical label SOURCE-BACKED Public Interest 25 Category RESEARCH Reader Depth TECHNICAL

Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.

Public Interest components
Recognizable Entity Score 0 Practical Impact Score 0 Novelty Interest Score 70 Consequence Score 34 Curiosity Score 16 Shareability Score 41

VQV surfaced this signal because it is recent, relevant to AI Agents, connected to arXiv.