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English(EN) Exploring the Cryptographic Limits of Transformer Networks

研究人员将密码函数映射到 Transformer 网络

研究人员探索了 Transformer 网络在密码学上的能力,研究这些模型是否可以实现特定的密码函数。该研究将 Keccak 函数、Merkle--Damgard 构造和 Merkle 树等密码构造映射到 Transformer 架构,推导出电路宽度和深度的缩放定律。这项工作建立了一种评估 Transformer 计算能力的方法,并为给定大小的 Transformer 可以计算的内容提供了建设性的上限,有助于对 AI 系统的能力进行原则性评估。 AI

影响 确立了 Transformer 计算能力的理论极限,有助于能力评估。

排序理由 该集群包含一篇学术论文,详细介绍了对 Transformer 网络能力的研究。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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

研究人员将密码函数映射到 Transformer 网络

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该集群包含一篇学术论文,详细介绍了对 Transformer 网络能力的研究。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Stefan Domunco, Andis Draguns, Philip Torr, Isaac Robinson, Christian Schroeder de Witt ·

    探索 Transformer 网络在密码学上的极限

    arXiv:2606.29389v1 Announce Type: cross Abstract: In recent work it has been shown that colluding AI agents can use steganographic methods to exchange malicious information. Whether a transformer can implement steganographic methods depends on what cryptographic functions it can …