Reasoning Concentrates Errors, and Self-Consistency Never Notices

arXiv cs.AISeptember 29, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2609.32035v1 Announce Type: new Abstract: Self-consistency assumes that independent samples disagree when a model is unsure, so agreement is evidence of correctness. Holding weights fixed and toggling only a reasoning mode, over five benchmarks and 74,944 samples, we show that reasoning concentrates a model's errors: the probability that two independently drawn wrong answers coincide rises in all ten dataset-scale comparisons (p = 0.00098), and in nine of nine after restricting both arms to the problems each gets wrong. Where the answer space is unbounded, reasoning cuts the distinct answers produced to 0.43-0.65 of the non-reasoning count; where it is bounded, both arms hold an identi

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