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English(EN) Tracing Money Flows in the Multi-Token Cryptocurrency Network

新的基准和模型解决了多跳加密货币资金追踪问题 · 2篇论文

两篇新的研究论文均于2026年10月12日提交,旨在解决加密货币资金流追踪的复杂挑战。第一篇论文介绍了CryptoFlowBench,这是一个旨在评估用于非法资金追踪的多跳推理的基准,并提出了ChainSleuth,一个使用图工具进行自适应追踪的代理。第二篇论文提出了一个面向交易的图模型,用于追踪多代币加密货币网络内的资金流,并展示了其在Aave借贷偿还流中的应用,同时强调了频繁的代币转换序列。 AI

影响 这些论文通过改进追踪非法加密货币交易的方法,提升了AI在金融取证和安全方面的能力。

排序理由 两篇发表在arXiv上的学术论文,提出了新的加密货币资金追踪基准和方法。

在 arXiv cs.IR (Information Retrieval) 阅读 →

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新的基准和模型解决了多跳加密货币资金追踪问题 · 2篇论文

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两篇发表在arXiv上的学术论文,提出了新的加密货币资金追踪基准和方法。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Runang He, Tongya Zheng, Jing Cao, Yucheng Ying, Shunyu Liu, Bingde Hu, Yang Gao, Zeyuan Hu, Jianrong Zhang, Mingli Song ·

    CryptoFlowBench:用于加密货币基金追踪的区块链多跳推理基准测试

    arXiv:2610.16449v1 Announce Type: cross Abstract: Pseudonymous accounts and complex smart-contract ecosystems substantially hinder the tracing of illicit cryptocurrency fund flows. Existing Graph Neural Networks (GNNs) have achieved promising performance in blockchain fraud detec…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Célestin Coquidé ·

    追踪多代币加密货币网络中的资金流

    Tracing money flows in cryptocurrency transaction networks is challenging because funds can move across accounts, transactions, and token layers. We propose a transaction-aware graph in which nodes represent account--asset states within transactions, while edges encode observed t…