Ablation-Reversible Heads Don't Transfer: A Stress Test for Mechanistic Role Claims in Transformers

Abstract:In mechanistic interpretability, attention heads are commonly elevated to role claims (e.g., "this head represents addition") when they are necessary for a behavior, encode it linearly, and recover that behavior when restored after ablation. We show this evidence is insufficient: across three 7-8B instruction-tuned models and five computation families, heads passing all three checks routinely fail to transfer the computation when their activations are patched into a different prompt under matched controls. We introduce KID (Knowing / Intent / Doing), a role-assignment lens for attention heads, and pair it with a three-stage pipeline: capability-selective screening (CSS), singular value decomposition (SVD), and activation transduction under matched controls. Our results document a preliminary role taxonomy (including prompt-trajectory stabilizers, answer-side logit-bias heads, and soft computation-pattern carriers) and show that the same-answer control (a transduction target sharing the answer string but not the requested computation) is an underused check that exposes broad state transfer masquerading as semantic specificity.

Artificial Intelligence (cs.AI)

arXiv:2606.08292 [cs.AI]

(or arXiv:2606.08292v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2606.08292 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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