Looped small decision model reportedly scores 72.0% versus 58.4% for a nonlooped counterpart

A post summarizing a paper says SanSi repeatedly runs the layers of Ouro-1.4B and checks option probabilities after each of up to eight loops. Across 10,027 test decisions, it reports 72.0% accuracy versus 58.4% for a same-shape model without loops, at 7.7 times the compute. On liar chains longer than any seen in training, the post says SanSi reached 72.6%, compared with 50.0% for a 4.2B single-pass model.