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depth-recurrent Transformer

technology3 mentionslast seen Nov 7, 2026

A Transformer architecture that decouples computational depth from parameter count by iterating a shared-weight block, enabling variable-depth reasoning with flat memory cost and linear latency.

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depth-recurrent Transformer

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depth-recurrent TransformersupersedesChain-of-Thought

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preprintarXivSep 15, 2026Thinking Deeper, Not Longer: Memory-Efficient Test-Time Reasoning with Depth-Recurrent Transformers for Compositional Generalization
Standard Transformers have a fixed computational depth, limiting their ability to generalize to tasks that require variable-depth reasoning. The usual remedy, Chain-of-Thought (CoT), spends tokens to reason, inflating the key--value cache and making latency grow with the step count, so memory becomes the limiting cost when reasoning is served over large query batches.