English(EN) Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study

研究人员发现，大型语言模型在比特币交易分析方面展现出强大潜力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 04:00

研究人员探讨了大型语言模型（LLMs）在分析加密货币交易中的应用，重点关注比特币。他们开发了一个框架来评估LLM的能力，包括一种名为LLM4TG的新图表示格式和一种名为CETraS的采样算法，这些共同减少了分析交易图所需的token数量。实验表明，LLMs在识别基本交易信息和识别特征方面取得了高准确率，即使在标记数据有限的情况下，在分类任务中也表现出色，尽管解释并不总是完全准确。 AI

影响展示了LLMs在金融交易分析等专业领域的处理能力，有望提高欺诈检测和可解释性。

排序理由详细介绍新方法论和实验结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Yuchen Lei, Yuexin Xiang, Rafael Dowsley, Tsz Hon Yuen, Andreas Deppeler, Jiangshan Yu, Qin Wang, Kim-Kwang Raymond Choo · 2026-10-07 04:00

用于加密货币交易分析的大型语言模型：一项比特币案例研究

arXiv:2501.18158v4 Announce Type: replace-cross Abstract: Cryptocurrencies are widely used, yet current methods for analyzing transactions often rely on opaque, black-box models. While these models may achieve high performance, their outputs are usually difficult to interpret and…

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报道来源 [1]

用于加密货币交易分析的大型语言模型：一项比特币案例研究

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