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When generating the next token in a sequence, applying an operator that identifies the K items with the highest values with the parameter K set to 1 will produce a different set of candidate tokens than simply selecting the single token with the highest probability.
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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
Comprehension in Revised Bloom's Taxonomy
Cognitive Psychology
Psychology
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Mathematical Definition of Top-K Token Selection
Formal Derivation of the Top-k Selection Pool
A language model is generating text and needs to decide on the next token. It has calculated the following probabilities for a small set of possible tokens:
{'over': 0.12, 'the': 0.35, 'a': 0.28, 'under': 0.05, 'quick': 0.20}. If an operator is applied to this set to identify theK=3tokens with the highest probability values, which set of tokens will be returned?Analyzing the Impact of the 'K' Parameter on Token Selection
When generating the next token in a sequence, applying an operator that identifies the
Kitems with the highest values with the parameterKset to 1 will produce a different set of candidate tokens than simply selecting the single token with the highest probability.