Flow Reasoning Models repo out: stable attractors solve Sudoku-Extreme with 44× fewer FLOPs
alec_helbling · x · 2026-09-03
Alec Helbling and colleagues released the repository for their Flow Reasoning Models (FRMs) paper, with implementation code coming soon.
Key claim: FRMs shape correct solutions into stable attractors, reaching EqR's peak Sudoku-Extreme solve rate with 44× fewer inference FLOPs. Co-authors include Mauro Martino, Duen Horng (Polo) Chau, Nima Dehmamy, and Hendrik Strobelt.
Related event: Flow Reasoning Models Solve Sudoku With 44x Less Compute(4 posts)→
More from Research
- Action Chunking Boosts Contrastive RL Even in Fully Online RL, Study Finds — ben_eysenbach · 2026-09-03
- Coding models are running out of data — PL researchers propose 'intent computing' as the fix — LingmingZhang · 2026-09-03
- davidad Backs Call to Ban Naive RLVR: 'Everything Should Be Model-Graded' — davidad · 2026-09-03
- Computerphile Deep Dive: How Watermarks Track AI-Generated Content — Computerphile · 2026-09-03
- TrafficLab 3D builds digital-twin traffic visualizations from CCTV footage and Google Maps — tom_doerr · 2026-09-03
- SOCO benchmark debuts at ECCV 2026: 1M+ pairs probe how vision models grasp object structure — HirokatuKataoka · 2026-09-03