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Explanation Multiplicity: Circuit-Level Interpretability Evidence Does Not Survi

BACKGROUND
1 SIGNALFIRST DETECTED 17 August 2026
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17 Aug
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23 Mar
Pitfalls in Evaluating Interpretability Agents

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Interpretability without actionability: mechanistic methods cannot correct language model errors despite near-perfect internal representations

arXiv:2603.18353v1 Announce Type: new Abstract: Language models encode task-relevant knowledge in internal representations that far exceeds their output performance, but whether

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Representational Simplicity and Circuit Size Dissociate in a Threshold-Dependent Way: A Controlled Test via Adversarial Training

arXiv:2609.35890v1 Announce Type: new Abstract: Sparse-autoencoder decomposability and concentrated feature attribution are increasingly treated as evidence that a model's

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Prediction certification cannot replace explanation certification: a competence envelope for trustworthy AI under compound stress

arXiv:2608.20825v1 Announce Type: new Abstract: Artificial intelligence systems increasingly make consequential judgments - which patient is deteriorating, which building is safe

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