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English(EN) Beyond But-for Test: Counterfactual Explanation in Abstract Argumentation via Actual Causality (Extended Version)

新研究探索人工智能领域的高级反事实解释方法

作者 PulseAugur 编辑部 · [3 个来源] ·

两篇新研究论文探索了人工智能领域高级反事实解释方法。第一篇论文来自 arXiv cs.AI，引入了一个基于干预的抽象论证框架，该框架超越了“事后诸葛亮”检验来识别实际原因。第二篇论文来自 arXiv cs.LG，提出了 DISCOVER，一个模型无关的分布反事实解释求解器，它使用一种提议-选择搜索范式来处理不可微分模型。 AI

影响 这些论文通过提供更鲁棒的模型决策理解方法，推动了人工智能可解释性领域的发展。

排序理由 两篇在 arXiv 上发表的学术论文，详细介绍了人工智能解释的新方法。

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

新研究探索人工智能领域的高级反事实解释方法

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两篇在 arXiv 上发表的学术论文，详细介绍了人工智能解释的新方法。
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报道来源 [3]

  1. arXiv cs.AI TIER_1 English(EN) · Pavel Iakovets, Liyanapathiranage Sudeepika Wajirakumari Samarathunga, Martin Thomas Horsch, Fadi Al Machot ·

    PACE：一个用于合理且可操作的逆事实解释的神经符号框架

    arXiv:2607.01306v1 Announce Type: new Abstract: Counterfactual explanations explain machine learning predictions by identifying minimal input changes that would alter a model's decision. Although many existing methods successfully generate prediction-changing alternatives, they o…

  2. arXiv cs.AI TIER_1 English(EN) · Siyi Liu, Muyun Shao, Beishui Liao ·

    超越反事实测试：通过实际因果关系实现抽象论证中的反事实解释（扩展版）

    arXiv:2606.31080v1 Announce Type: cross Abstract: Counterfactual explanation in abstract argumentation calls for an answer to the what-if query: would the topic argument still be accepted if the status of certain other arguments were changed? Existing approaches are limited to th…

  3. arXiv cs.LG TIER_1 English(EN) · Yikai Gu, Lele Cao, Bo Zhao, Lei Lei, Lei You ·

    DISCOVER：用于分布反事实解释的求解器

    arXiv:2603.16436v2 Announce Type: replace Abstract: Counterfactual explanations (CE) explain model decisions by identifying input modifications that lead to different predictions. Most existing methods operate at the instance level. Distributional Counterfactual Explanations (DCE…

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