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English(EN) RAGas: Retrieval-Augmented Gas Optimization for Smart Contracts with Continuous Knowledge Integration

RAGas框架优化以太坊智能合约的气体效率

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了RAGas，一个旨在优化以太坊智能合约中气体使用量的新型框架。该系统利用检索增强生成（RAG）和大型语言模型来识别并自动纠正导致高执行费用的代码效率低下问题。实验表明，RAGas可以在保持功能等效性的同时，将气体消耗量减少高达11%，解决了持续利用不断变化的 গ্যাস使用模式的不足之处。 AI

影响 该框架可能显著降低以太坊上的交易成本，使去中心化应用程序更易于访问且更具成本效益。

排序理由 该集群描述了一篇关于优化智能合约的新型框架的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

RAGas框架优化以太坊智能合约的气体效率

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该集群描述了一篇关于优化智能合约的新型框架的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yishun Wang, Wenjin Yi, Wenkai Li, Zongwei Li, Xiaoqi Li ·

    RAGas：用于智能合约的检索增强气体优化，支持持续知识集成

    arXiv:2608.15857v1 Announce Type: new Abstract: Ethereum is now integral to mission-critical sectors, including finance, healthcare, and supply chain management. Execution fees, commonly referred to as Gas, scale with the computational complexity of their functions. Smart contrac…

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