Are Sparse Autoencoder Benchmarks Reliable?
DGX agentarXiv:2605.18229v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) are a core interpretability tool for large language models, and progress on SAE architectures depends on benchmarks that re