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University of Science and Technology of China
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EvolveNet reveals that decentralized evolution of agent harnesses can lead to substantial performance gains by leveraging localized experience rather than relying on centralized optimization.
A single misleading document can drastically reduce deep research agents' accuracy by up to 88%, exposing a critical vulnerability in their evidential reasoning capabilities.
Harnesses can evolve in real-time during evaluation, leading to significant performance gains without retraining the underlying model.
