Formula for Token Sampling in Autoregressive Models

Applying Token Sampling in Text Generation

An autoregressive language model has processed the input sequence 'The cat sat on the' and has calculated the following conditional probability distribution for the next token: P('mat'|context) = 0.6, P('rug'|context) = 0.3, P('floor'|context) = 0.08, P('sky'|context) = 0.02. If the model then samples a token from this distribution, which of the following statements is most accurate?

In autoregressive text generation, after the model computes the conditional probability distribution for the next token, the sampling process always selects the token with the highest probability score.