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Definition of the Top-k Selection Pool
In top-k sampling, the selection pool, denoted as for a given step , is the set of the top-k most probable tokens from which the next token is chosen. This pool is formally defined as:

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Ch.5 Inference - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Top-k Sampling Process
Comparison of Top-p and Top-k Sampling
A language model is generating text and has calculated the following probabilities for potential next tokens:
mat(0.45),rug(0.25),floor(0.15),table(0.10), andwindow(0.03). If the model uses a decoding strategy where it first identifies the 3 most probable tokens and then randomly samples one token from only that reduced group, which of the following statements is true?Effect of Candidate Pool Size on Text Generation
A language model is configured to generate text by first selecting a fixed number of the most probable next tokens and then sampling from only that reduced set. If the fixed number of tokens to consider is significantly decreased (e.g., from 100 to 5), what is the most likely impact on the generated text?
argTopK Function
Definition of the Top-k Selection Pool
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Softmax Renormalization in Top-k Sampling
Learn After
A language model is generating text and at a certain step, it predicts the following probabilities for the next token from its vocabulary: {'the': 0.4, 'a': 0.2, 'cat': 0.15, 'dog': 0.1, 'ran': 0.08, 'sat': 0.07}. If the model is configured to use a sampling strategy where the next token is chosen from the 3 most probable candidates, which set represents the selection pool for this step?
Constructing the Top-k Selection Pool
If the parameter 'k' is set to 1, the resulting selection pool will contain only the single most probable token, making the sampling process from this pool effectively equivalent to a greedy search at that step.