General Notation for Conditional Probability in Sequence Generation
The notation represents the conditional probability of a subsequent item 'y' occurring, given a context of preceding items, which can include both initial inputs (x's) and previously generated outputs (y's). This is a general way to express the core calculation in sequence generation models, where the probability of the next item depends on everything that came before it.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Ch.2 Generative Models - Foundations of Large Language Models
Learn After
A language model is generating text and has so far produced the sequence 'The sky is'. The model now needs to calculate the likelihood of the next word being 'blue'. Which of the following mathematical expressions correctly represents the probability of the next word being 'blue', given the preceding words?
Conditional Probability in Sequence-to-Sequence Generation
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Applying Conditional Probability Notation in Text Summarization