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cs.LG2026
Interpreting Language Model Parameters
Lucius Bushnaq, Dan Braun, Oliver Clive-Griffin +5
Mechanistic interpretability aims to uncover how neural networks use their parameters to implement their impressive neural algorithms. Although previous work has uncovered substant…
cs.LG2026
Targeted Recovery of Weight-Space Mechanisms From Neural Networks
Antoine Vigouroux, Lee Sharkey
Parameter decomposition (PD) decomposes neural networks into interpretable computational components that faithfully reflect the original network's operations. However, scaling PD t…