Recent research demonstrates that applying matrix orthogonalization to mLSTM memory readouts significantly improves performance on noisy associative recall tasks. This technique prevents dominant memory features from overshadowing weaker ones, providing a more efficient alternative to high-overhead transformer attention mechanisms.