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By turning Mathlib PR histories into a supervised signal, MathlibPR provides a step toward reviewer assistants and reward models that could help evaluate PRs and steer LLMs toward producing merge-ready Mathlib contributions.
Self-evolving agents improve through repeated cycles of modification and evaluation. However, existing methods receive feedback on modifications only after costly evaluations, and aggregate scores may obscure distinctions between failures that require different repairs. We introduce predictive self-evolution through an...
The core conclusion indicates that single-point prediction accuracy alone cannot determine the overall efficiency of signal control systems, instead, uncertainty-aware phase-level optimization can simultaneously enhance traffic operation efficiency and operational stability.
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