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Forming the Candidate Set in a Search Algorithm
An algorithm is generating a sequence using a search process that keeps track of the 2 most likely options at each step (K=2). At a certain point, it considers extending the current options, resulting in four potential new sequences with the following scores (higher is better):
- 'The cat sat on' (Score: 0.9)
- 'The cat sat by' (Score: 0.6)
- 'The dog ran to' (Score: 0.8)
- 'The dog ran from' (Score: 0.5)
According to the procedure for forming the candidate set for the next step, which sequences will be included in this set?
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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
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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.