Riding the Fixed-Point Curve: Image Classification in the Continuous Thought Machine
Analyzes the Continuous Thought Machine's repeated updates during image classification. Finds that its hidden states follow moving fixed points and that much of its attention schedule is shared across images.
First public: · Added to this list: October 18, 2026
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ArXiv preprint
arXiv:2610.19220 · Initial submission: 2026-10-13
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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.
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.
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