研究人员开发了一种名为TED的新型图神经网络模型，以增强逃税检测能力。该模型通过利用异构图和关联方交易信息来解决现有方法的局限性，这些信息在税务场景中至关重要但常被忽视。TED采用分层注意力机制来捕捉这些复杂交易群体更深层次的结构和语义洞察，旨在过滤噪声并提高检测准确性。 AI
影响 这项研究引入了一种新颖的图神经网络方法，通过分析复杂的交易关系，可以提高逃税检测的准确性和效率。
排序理由 该集群包含一篇详细介绍特定任务新模型的学术论文。
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arXiv:2605.26984v1 Announce Type: new Abstract: Tax evasion causes severe losses of government revenues and disturbs the economic order of fair competition. To help alleviate this problem, the latest tax evasion detection solutions utilize expert knowledge to extract features and…
Tax evasion causes severe losses of government revenues and disturbs the economic order of fair competition. To help alleviate this problem, the latest tax evasion detection solutions utilize expert knowledge to extract features and then train classifiers to determine whether a c…