StateLoop: Persistent State for Looped Transformers
Gives each token a persistent state alongside the output of a shared transformer backbone. Learned gates control what the state retains across loops, and separate readouts feed it into later loops and the final prediction.
First public: · Added to this list: November 2, 2026
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Recurrent reasoning — Repeat parts of the model or keep intermediate information in memory while working through a problem. Some methods also learn how many passes to run.