1 citations · 1 across the 5 of their papers we have counts for
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Mathematical Models of Computation in Superposition
Kaarel Hänni, Jake Mendel, Dmitry Vaintrob +1
Superposition -- when a neural network represents more ``features'' than it has dimensions -- seems to pose a serious challenge to mechanistically interpreting current AI systems.…
The Local Interaction Basis: Identifying Computationally-Relevant and Sparsely Interacting Features in Neural Networks
Lucius Bushnaq, Stefan Heimersheim, Nicholas Goldowsky-Dill +7
Mechanistic interpretability aims to understand the behavior of neural networks by reverse-engineering their internal computations. However, current methods struggle to find clear…
Using Degeneracy in the Loss Landscape for Mechanistic Interpretability
Lucius Bushnaq, Jake Mendel, Stefan Heimersheim +5
Mechanistic Interpretability aims to reverse engineer the algorithms implemented by neural networks by studying their weights and activations. An obstacle to reverse engineering ne…