Deeper Backpropagation or More Updates? Training Looped Language Models Across Budgets
Compares short and long backpropagation windows in looped language models at matched token and training-time budgets. Extra updates favor shorter windows at small budgets, but that advantage shrinks as training grows.
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.
Analysis and evaluation — Measure how well these methods work, investigate what their internal computation does, and identify where they fail. This includes experiments, studies of model internals, and mathematical results.