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Applying Selection and Pruning in Text Generation
In a text generation model, after evaluating potential next words for the sequence 'The cat sat on the', the following candidates and their probabilities are produced: {'mat': 0.55, 'couch': 0.25, 'floor': 0.12, 'table': 0.06, 'rug': 0.02}. If the model is configured with a selection width of K=3, which words are discarded (pruned) in this step? Briefly explain your reasoning.
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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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In a text generation process, a set of potential next words and their calculated probabilities are ranked as follows:
{'the': 0.45, 'a': 0.25, 'his': 0.15, 'her': 0.10, 'its': 0.05}. If the process uses a fixed width of K=3 to select the most likely candidates, which words are kept and which are discarded (pruned)?Impact of Search Width on Text Generation
Applying Selection and Pruning in Text Generation