Expansion Stage in Top-k Sampling

Ranking and Pruning Stage in Top-k Sampling

A language model is generating the next word in a sentence and has calculated the probabilities for five potential words: 'house' (0.4), 'car' (0.3), 'boat' (0.15), 'plane' (0.1), and 'train' (0.05). The model uses a sampling method where it first ranks these words by probability, keeps only a specific number of the top-ranked words, renormalizes their probabilities to sum to 1, and then samples from this smaller set. How would decreasing the number of top-ranked words kept (e.g., from 4 to 2) most likely affect the generated text over time?

A language model is using a specific decoding method to generate the next token in a sequence. Arrange the following actions into the correct chronological order.

Ranking Stage in Top-k Sampling

Selection and Sampling Stage in Top-k Sampling

Output Stage in Top-k Sampling

Output Stage in Top-k Sampling

Applying a Probabilistic Filtering Method