A system generates four candidate outputs in response to a user's prompt. A separate evaluation model then assigns a quality score to each candidate, where a higher score indicates a better response. The system's selection rule is to choose the candidate that receives the maximum score. Given the scores below, which candidate will be selected as the final output?
- Candidate A: Score = 0.85
- Candidate B: Score = 0.91
- Candidate C: Score = 0.74
- Candidate D: Score = 0.23
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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
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Empirical Science
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Argmax Formula for Best Candidate Selection in BoN Sampling
A system generates four candidate outputs in response to a user's prompt. A separate evaluation model then assigns a quality score to each candidate, where a higher score indicates a better response. The system's selection rule is to choose the candidate that receives the maximum score. Given the scores below, which candidate will be selected as the final output?
- Candidate A: Score = 0.85
- Candidate B: Score = 0.91
- Candidate C: Score = 0.74
- Candidate D: Score = 0.23
Consider the process of selecting the best output from a set of N candidates, where a reward model
rscores each candidateŷ_ibased on an inputx. The selection is represented by the formula:ŷ_best = max{r(x, ŷ_1), ..., r(x, ŷ_N)}. This formula implies that the final output,ŷ_best, is a numerical value representing the highest score.Diagnosing a Mismatch in Automated Selection