Masanori Koyama

Positional encodings aren't just about position - they fundamentally prevent mean-field transformers from collapsing into meaningless single-point token distributions.

Ditch the energy functions: C-voting unlocks better test-time reasoning in recurrent models by simply picking the most confident trajectory.

Forget Transformers; this new recurrent architecture learns more stable representations and generalizes better out-of-distribution by interleaving fast latent updates with slower, self-organizing observation processing.