Matryoshka NLAs frontload reconstruction details for sharper model interpretability
A new "Matryoshka" NLA approach trains activation verbalizers to place the most informative reconstruction tokens at the beginning of the string. This front‑loading improves downstream tasks like suffix prediction and modestly boosts eval‑awareness detection, offering a clearer window into model internals.