Causal Latent Workspaces for Looped Transformers
Adds a small, content-addressed memory to a looped transformer, rebuilding causal prefix summaries between shared-layer passes. Tests whether this extra information path improves next-byte prediction under matched parameter and training budgets.
First public: · Added to this list: October 22, 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.