Mechanistic interpretability metrics favor wrong circuits, study finds
A new study identifies a fundamental problem in mechanistic interpretability research: the metrics used to validate circuit discovery can favor incorrect explanations of model behavior. Researchers demonstrate that intervention-based faithfulness metrics may select circuits that match model outputs while capturing less of the actual computational logic, creating what they call an objective-level recovery gap. Testing across multiple benchmarks reveals this gap persists even when circuits are equally sized, suggesting that current automated discovery methods may be systematically recovering the wrong mechanisms. This challenges a core assumption in interpretability work and has direct implications for how researchers should design validation frameworks when trying to reverse-engineer neural network internals.
Modelwire context
ExplainerThe paper isolates a specific failure mode: intervention-based metrics can reward circuits that produce correct outputs while missing the actual computational steps the model uses. This is distinct from prior work showing circuits explain successes but not failures; here, equally-sized circuits can both match outputs while one captures genuine mechanism and the other doesn't.
This extends the critique from 'Rethinking Circuit Evaluation' (late September) which found ablation-based validation incomplete. That work showed circuits could reproduce correct answers while staying silent on error patterns. This new paper goes further: it shows the validation metric itself can systematically favor wrong mechanisms even when both circuits match outputs equally well. The pattern across recent coverage (the math traces paper, the medical evidence work, the CoT verification audit) is consistent: surface-level correctness metrics conceal whether models are actually doing what we think they're doing. Interpretability research is discovering that its own measurement tools may be measuring the wrong thing.
If InterpBench (the benchmark mentioned in the entities) releases updated validation protocols within six months that weight mechanism recovery alongside output fidelity, that signals the field is taking this seriously. If major circuit discovery papers published after this date continue using only intervention-based faithfulness without addressing the recovery gap, that suggests the finding hasn't shifted practice yet.
Coverage we drew on
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Modelwire summarizes, we don’t republish. arXiv cs.LG originally reported this story as “Are We Recovering Mechanisms? Objective-Level Recovery Gaps in Mechanistic Interpretability”. The full content lives on arxiv.org. If you’re a publisher and want a different summarization policy for your work, see our takedown page.