Unverified50% confidenceFactExact time
Greedy decoding always selects the highest-probability token, so after 'The' it necessarily chooses 'moon'; sampling decoding, however, draws randomly according to probability weights and may select low-probability tokens such as 'lunar'.
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11/5/2026
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Related Claims
VerifiedGreedy decoding always selects the token with the highest probability, while random sampling draws from the probability distribution, which means the same prompt may yield different responses.72% similarVerifiedGreedy decoding selects the token with the highest current probability at every step, which tends to accumulate systematic bias in multi-step tasks because local optima do not equal global optima.69% similarUnverifiedThe temperature parameter controls sampling randomness: the lower the value, the more deterministic the output; near 0, the model tends to choose the highest-probability token, suitable for code generation, SQL generation, and other scenarios requiring reproducibility.59% similarUnverifiedRewards that are too sparse (scored only at the end of an episode) make it very difficult for the agent to obtain effective gradients through random trial and error.58% similarUnverifiedIn the causal randomized strategy framework, the decision of which coordinates to sample in round t can only depend on information already generated in the previous t-1 rounds and cannot foresee future randomness.58% similar
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