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Causal abstraction

2 open-access journal articles on causal abstraction, published in 2026 in Life of Research. Every record is free to read and download, with a permanent link and a ready-made citation.

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Journal article

Circuits Are Estimates, Not Mechanisms: A Recovered Subgraph Is One Draw From a Class Set by the Ablation, the Dataset and the Grain, the Results That Defend Circuits Hold at the Level of That Class, and What Ablation Evidence Licenses at Each Level

A circuit in a language model is usually presented as the mechanism by which the model performs a task: a sparse subgraph, found by ablation or patching, that reproduces the behaviour when everything else is knocked out. A second body of work, mostly from 2024 to 2026, reports that the subgraph…

Cite Related research LOR-00098 · 9 views · 13 downloads
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Journal article

Dictionaries Without Ontologies: What a Sparse Autoencoder Latent Is Evidence For, Why Decodability, Use and Reproducibility Do Not Add Up to Canonicity, and the Identifiability Premise No Real-Model Result Has Checked

Sparse autoencoders are now the default instrument for decomposing language model activations, and their latents are routinely reported as the model's features: units the network itself uses, which a wide enough dictionary has pulled out of superposition. This paper asks what a latent is evidence…

Cite Related research LOR-00096 · 7 views · 7 downloads
PDF405.3 KB

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