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An LLM is tasked with completing the input sequence x = 'The best way to learn a new skill is'. During the inference process, a search algorithm considers several potential continuations, such as y1 = 'to practice consistently', y2 = 'by reading a book', and y3 = 'through immersive experience'. How are these potential continuations best described within the context of the search problem?
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Ch.5 Inference - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
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Analysis in Bloom's Taxonomy
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Search Space in LLM Inference
An LLM is tasked with completing the input sequence
x = 'The best way to learn a new skill is'. During the inference process, a search algorithm considers several potential continuations, such asy1 = 'to practice consistently',y2 = 'by reading a book', andy3 = 'through immersive experience'. How are these potential continuations best described within the context of the search problem?Justification for Hypothesis Simplification
During language model inference, a 'hypothesis' refers exclusively to a potential output sequence, and the input sequence is not considered part of its formal definition.