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DRA outputs are surprisingly variable, with inference and early-stage decisions being the biggest culprits, but structured outputs and ensemble querying can significantly reduce this stochasticity.
LLMs can be taught to reason more faithfully and accurately by training them to produce reasoning steps that other models can easily follow.
