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cs.LG2025
Studying Cross-cluster Modularity in Neural Networks
Satvik Golechha, Maheep Chaudhary, Joan Velja +2
An approach to improve neural network interpretability is via clusterability, i.e., splitting a model into disjoint clusters that can be studied independently. We define a measure…
cs.LG2024
Evaluating Open-Source Sparse Autoencoders on Disentangling Factual Knowledge in GPT-2 Small
Maheep Chaudhary, Atticus Geiger
A popular new method in mechanistic interpretability is to train high-dimensional sparse autoencoders (SAEs) on neuron activations and use SAE features as the atomic units of analy…