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Equation 10 · Running an Interpretability Investigation That Holds Up

What does this equation mean?

S(C,C′)=Δ(C)−Δ(C′).S(\mathcal{C}, \mathcal{C}') = \Delta(\mathcal{C}) - \Delta(\mathcal{C}').

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Inputs and operationsΔ(C) - Δ(C')
Result or conditionS(C, C')
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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.

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SS

Symbol S

S is part of the quantity the equation computes from the expression on the right.

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C\mathcal{C}

Symbol C

C is an argument of the function-like quantity on the left; its role is set by that function’s stated inputs.

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Δ\Delta

Symbol Δ

Δ is one of the signed contributions combined to compute the quantity on the left.

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=

=

The expressions on both sides represent the same quantity under the stated assumptions.

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subtraction

subtraction

Subtract the following term or group from the preceding one. A leading minus marks a negative quantity.

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How to interpret it

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What the article says around this equation

The defence against this is a control condition run alongside the target one, not after it: intervene identically on a component set C\mathcal{C}' matched to the target set C\mathcal{C} in size, depth and baseline activation statistics, but which the hypothesis explicitly predicts should have no effect, and compare S(C,C′)=Δ(C)−Δ(C′)S(\mathcal{C}, \mathcal{C}') = \Delta(\mathcal{C}) - \Delta(\mathcal{C}'). A specificity margin S that is small relative to the run-to-run variance means the intervention is detecting generic sensitivity to perturbation somewhere in the network, not the mechanism under test — which is exactly the failure mode the subspace illusion exhibits. Reporting Δ(C)\Delta(\mathcal{C}) alone, without the matched control alongside it, is reporting half…
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The defence against this is a control condition run alongside the target one, not after it: intervene identically on a component set C\mathcal{C}' matched to the target set C\mathcal{C} in size, depth and baseline activation statistics, but which the hypothesis explicitly predicts should have no effect, and compare S(C,C′)=Δ(C)−Δ(C′)S(\mathcal{C}, \mathcal{C}') = \Delta(\mathcal{C}) - \Delta(\mathcal{C}'). A specificity margin S that is small relative to the run-to-run variance means the intervention is detecting generic sensitivity to perturbation somewhere in the network, not the mechanism under test — which is exactly the failure mode the subspace illusion exhibits. Reporting Δ(C)\Delta(\mathcal{C}) alone, without the matched control alongside it, is reporting half an experiment.

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