adaptive-exit

This paper explores looped (recurrent) state-space language models using Mamba and hybrid Mamba-Transformer backbones, showing they outperform non-looped baselines on reasoning tasks and remain competitive under iso-parameter and iso-FLOPs pretraining, with adaptive exit-state selection improving intermediate-depth performance.