Author

Lucius Bushnaq

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#artificial intelligence Preprint Oct 2026

Interpreting Language Model Parameters

Mechanistic interpretability aims to uncover how neural networks use their parameters to implement their impressive neural algorithms. Although previous work has uncovered substantial structure in the intermediate representations that networks use, little progress has been made to understand how the parameters and nonl...

Lucius Bushnaq, Dan Braun, Oliver Clive-Griffin et al. · 4 citations · ⚡1

#machine learning Preprint Aug 2026

Functional Degeneracy in Neural Networks: Measurement and Pruning

This work quantifies functional degeneracy through the behavioral recovery rank, defined as the number of leading behavioral-Hessian eigendirections required to recover a trained model's performance, and finds that structural and magnitude pruning retain more degrees of freedom, even after the task is saturated.

M. Matveev, P. Esser, Ayush Bharadwaj et al. · 0 citations