10 citations · 10 across the 2 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2024★ 10 cited
Scaling and evaluating sparse autoencoders
Leo Gao, Tom Dupré la Tour, Henk Tillman +6
Sparse autoencoders provide a promising unsupervised approach for extracting interpretable features from a language model by reconstructing activations from a sparse bottleneck lay…
cs.LG2021
Differentiable Random Access Memory using Lattices
Adam P. Goucher, Rajan Troll
We introduce a differentiable random access memory module with performance regardless of size, scaling to billions of entries. The design stores entries on points of a chose…