Unverified50% confidenceFactExact time
High error rates in the early stages may cause the router to prematurely abandon certain experts whose answers could have brought high value once the correction function is learned, forming a self-reinforcing negative feedback loop.
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Long-term
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10/7/2026
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Related Claims
VerifiedAgents face the problem of error cascading: judgment errors in early steps are amplified exponentially with the number of iterations.78% similarVerifiedError cascading refers to small judgment deviations in early steps being progressively amplified as the reasoning chain extends, ultimately producing results far from what was intended.77% similarUnverifiedSelf-generated feedback from the model may produce misleading pseudo-insights, and validator quality affects feedback effectiveness, which remains an open question for this method.77% similarVerifiedWhen an autoregressive model produces an erroneous intermediate conclusion early in the reasoning chain, it causes subsequent steps to accumulate errors, forming an error accumulation effect.77% similar
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