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An algorithm is generating a sequence, keeping the 2 most likely partial sequences (the 'beam') at each step. At the current step, the beam contains sequence 'A' (score: -1.0) and sequence 'B' (score: -2.0). The algorithm then identifies the most likely next tokens to extend these sequences:
- For 'A', the next tokens are 'C' (score: -1.5) and 'D' (score: -1.6).
- For 'B', the next tokens are 'E' (score: -0.1) and 'F' (score: -0.2).
Given that scores are combined by addition, which of the following sets represents the top 2 new candidate sequences that are formed in this expansion step?
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Ch.5 Inference - Foundations of Large Language Models
Foundations of Large Language Models
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An algorithm is generating a sequence, keeping the 2 most likely partial sequences (the 'beam') at each step. At the current step, the beam contains sequence 'A' (score: -1.0) and sequence 'B' (score: -2.0). The algorithm then identifies the most likely next tokens to extend these sequences:
- For 'A', the next tokens are 'C' (score: -1.5) and 'D' (score: -1.6).
- For 'B', the next tokens are 'E' (score: -0.1) and 'F' (score: -0.2).
Given that scores are combined by addition, which of the following sets represents the top 2 new candidate sequences that are formed in this expansion step?
Forming the Candidate Set in a Search Algorithm
In a sequence generation algorithm that maintains a fixed number of top hypotheses at each step, the candidate set for the current step is formed by taking the newly generated sequences and adding them to the set of hypotheses from the previous step.