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English(EN) How Learning Governs Unlearning across the Memorization-Generalization Spectrum

机器遗忘研究强调数据删除的挑战

作者 PulseAugur 编辑部 · [2 个来源] ·

两篇新研究论文探讨了机器遗忘的复杂性，重点关注模型的学习过程如何影响其遗忘特定数据的能力。第一篇论文研究了“仅遗忘式遗忘”，即模型必须仅使用训练模型和需要遗忘的示例来删除数据，发现这个过程可能具有挑战性，并且可能需要模型保留比标准训练更多的信息。第二篇论文考察了记忆和泛化之间的谱系，证明高度依赖记忆的模型在发生遗忘时性能下降更大。两项研究都强调了在开发有效的遗忘方法时考虑学习动态的重要性。 AI

影响 这些研究表明，当前的遗忘方法可能不足，并强调需要新的方法来考虑模型的学习方式。

排序理由 两篇在arXiv上发表的关于机器遗忘技术的学术论文。

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机器遗忘研究强调数据删除的挑战

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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Luka Radi\'c, Vikrant Singhal, Amartya Sanyal ·

    为何仅遗忘式“不可学”需要记忆

    arXiv:2610.10519v1 Announce Type: new Abstract: Machine unlearning asks for a deletion algorithm whose output is close to retraining from scratch without the selected forget examples. In this work, we study forget-only unlearning, where the deletion algorithm receives only the tr…

  2. arXiv cs.AI TIER_1 English(EN) · Hwiyeong Lee, Hyelim Lim, Ingyu Bang, Hoki Kim, Taeuk Kim ·

    学习如何在记忆-泛化谱中控制遗忘

    arXiv:2610.08577v1 Announce Type: cross Abstract: While unlearning seeks to negate undesired capabilities acquired through learning, little research has examined how the way models learn shapes their subsequent unlearning. In this paper, we investigate this connection from the pe…

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