Equilibrium Reasoners learn task-conditioned neural attractors that treat solutions as stable latent points and reach 99.8 percent accuracy on Sudoku-Extreme through iterative residual descent.

🌀 Introducing 𝐄𝐪𝐮𝐢𝐥𝐢𝐛𝐫𝐢𝐮𝐦 𝐑𝐞𝐚𝐬𝐨𝐧𝐞𝐫𝐬 (𝐄𝐪𝐑) ! Feedforward models and weight-tied models behave very differently on hard reasoning generalization. EqR pushes this difference to the extreme by learning 𝐭𝐚𝐬𝐤-𝐜𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐞𝐝 𝐧𝐞𝐮𝐫𝐚𝐥 𝐚𝐭𝐭𝐫𝐚𝐜𝐭𝐨𝐫𝐬 . • Sudoku-Extreme: 99.8% • Maze: 93% #ICML2026