With shortcut-decorrelated training, bidirectional masking, and a corrective objective, depth scaling makes direct transformer reasoning over Horn clauses match CoT accuracy within the training horizon, but not beyond it.
Transformers provably solve parity efficiently with chain of thought
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The Scaling Properties of Implicit Deductive Reasoning in Transformers
With shortcut-decorrelated training, bidirectional masking, and a corrective objective, depth scaling makes direct transformer reasoning over Horn clauses match CoT accuracy within the training horizon, but not beyond it.