Sparse autoencoders uncover biologically interpretable features in protein language model representations

Proceedings of the National Academy of Sciences, Volume 122, number 34, August 2025.
Representations of interpretation of meaning derived from protein language models (PLMS) are crucial to improve confidence in the model, human explanation and collaboration in downstream applications. We take advantage of sparse self -enlisters and transcoders of …