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Applying the 1-Best Selection Method
A language model is generating the next word and has produced the following five candidate words with their associated probabilities: 'happy' (Pr = 0.41), 'sad' (Pr = 0.15), 'very' (Pr = 0.28), 'and' (Pr = 0.11), and 'is' (Pr = 0.05). Based on a process that selects only the single most likely candidate and discards the rest, identify which word is chosen for the output and which words are discarded.
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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
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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A language model is generating the next word in a sentence. After calculating the probabilities for several candidate words, it has the following set: 'the' (probability = 0.45), 'a' (probability = 0.25), 'my' (probability = 0.15), and 'your' (probability = 0.10). If the model uses a selection method where only the single most probable candidate is chosen and all others are discarded, which word will be selected for the final output?
Applying the 1-Best Selection Method
Inferring Probability from Model Output