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Evidence record 4692 · automatically gathered

Biological Plausibility and Representational Alignment of Feedback Alignment in Convolutional Networks

The feedback alignment (FA) algorithm offers a biologically plausible alternative to backpropagation (BP) for training neural networks yet notably fails to scale to convolutional architectures. Modifications have been proposed to address this limitation, but at questionable cost to biological plausibility. In this paper, we evaluate five learning algorithms including modified FA and standard BP, applied to the same convolutional architecture with the CIFAR-10 dataset. We provide a tripartite com

Record details

Published: 8 May 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Biotech
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Safety & alignment · Shared topic: Biotech

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How to cite this record

ethics.ai (8 May 2026), “Biological Plausibility and Representational Alignment of Feedback Alignment in Convolutional Networks,” evidence record 4692, https://ethics.ai/record/4692 (originally published by arXiv).

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