Beyond SAEs: Consistent Concept Discovery with Sparse Coding
Replaces the linear SAE encoder with per-sample sparse coding to learn dictionaries that stay consistent across training runs.
jinho-choi
Replaces the linear SAE encoder with per-sample sparse coding to learn dictionaries that stay consistent across training runs.
Sparse autoencoders for interpretable single-cell embeddings in hematology.
Sparse autoencoders expose how visual concepts are selectively remapped when vision models adapt to new domains.