sparse-autoencoder-training
Guides users in training and analyzing Sparse Autoencoders to uncover interpretable features in neural network activations.
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The sparse-autoencoder-training skill was audited on Feb 28, 2026 and we found 7 security issues across 1 threat category. Review the findings below before installing.
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External URL reference
SourceSKILL.md
| 327 | Browse pre-trained SAE features at [neuronpedia.org](https://neuronpedia.org): |
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External URL reference
SourceSKILL.md
| 360 | - [ARENA SAE Curriculum](https://www.lesswrong.com/posts/LnHowHgmrMbWtpkxx/intro-to-superposition-and-sparse-autoencoders-colab) |
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SourceSKILL.md
| 363 | - [Towards Monosemanticity](https://transformer-circuits.pub/2023/monosemantic-features) - Anthropic (2023) |
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External URL reference
SourceSKILL.md
| 364 | - [Scaling Monosemanticity](https://transformer-circuits.pub/2024/scaling-monosemanticity/) - Anthropic (2024) |
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SourceSKILL.md
| 365 | - [Sparse Autoencoders Find Highly Interpretable Features](https://arxiv.org/abs/2309.08600) - Cunningham et al. (ICLR 2024) |
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External URL reference
SourceSKILL.md
| 368 | - [SAELens Docs](https://jbloomaus.github.io/SAELens/) |
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External URL reference
SourceSKILL.md
| 369 | - [Neuronpedia](https://neuronpedia.org) - Feature browser |
Scanned on Feb 28, 2026
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/learn @davila7/mechanistic-interpretability-saelensGitHub Stars 22.3K
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Categorydevelopment
UpdatedMarch 29, 2026
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