How Much Gradient Does Truncated Backprop Lose in Looped Transformers?
Measures how much of the weight gradient is dropped when looped language models backpropagate through only their final iterations. Tracks how this changes during fine-tuning and tests whether the measurement predicts the resulting training loss.
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.
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.