English(EN) Denoising Models Develop Human-Like Perceptual Illusion Representations Across Architectures

去噪人工智能模型开发出感知错觉的内部表征

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-19 08:50

研究人员发现，在自然图像上训练的去噪深度神经网络，会开发出对人类感知错觉敏感的内部表征。这些表征存在于不同架构的特定层和通道中，去噪目标比架构本身更具影响力。虽然这些内部激活与人类亮度感知的心理物理模型相关，并随错觉强度而扩展，但将其注入生成流程并未产生可观察到的输出变化，研究人员因此称之为“感知幻影”。 AI

影响揭示了人工智能模型可以开发出感知现象的内部表征，即使这些表征未反映在输出中，这表明对模型内部运作有了更深入的了解。

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-07-19 08:50

Denoising模型在跨架构中开发出类似人类的感知错觉表征

Deep neural networks trained on natural images are shown to produce outputs consistent with human observers for brightness illusions. While this phenomenon has been documented across architectures, all evidence, to date, is measured at the output level: restored pixels, decoded t…

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Denoising模型在跨架构中开发出类似人类的感知错觉表征

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