Formula for the Candidate Set in Beam Search
In the expansion step of beam search, a set of candidate sequences for step i, denoted , is formed. This set consists of the K new hypotheses generated by extending the previous step's sequences. It is formally defined as the collection of the top K candidate sequences: where each is a newly formed sequence.
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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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Formula for the Candidate Set in Beam Search
In a text generation process, a single partial sequence is being expanded. The current sequence is 'The sun is shining', and the three most probable next words have been identified as 'brightly', 'today', and 'and'. Based on this information, what will be the new set of candidate sequences to consider for the next step?
Error Analysis in Sequence Expansion
In a text generation process, several partial sequences (parent hypotheses) are being considered. For each parent hypothesis, the three most probable next tokens have been identified. Match each parent hypothesis to its correctly constructed set of new, longer candidate sequences.
Learn After
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.