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cs.LG2025★ 1 cited
MIB: A Mechanistic Interpretability Benchmark
Aaron Mueller, Atticus Geiger, Sarah Wiegreffe +20
How can we know whether new mechanistic interpretability methods achieve real improvements? In pursuit of lasting evaluation standards, we propose MIB, a Mechanistic Interpretabili…
cs.LG2024
Missed Causes and Ambiguous Effects: Counterfactuals Pose Challenges for Interpreting Neural Networks
Aaron Mueller
Interpretability research takes counterfactual theories of causality for granted. Most causal methods rely on counterfactual interventions to inputs or the activations of particula…