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Example of a Permuted Sentence with Non-Sequential Indexing
This example demonstrates a sentence where words are indexed in a non-sequential, or permuted, order. In the sentence The5 kitten7 is6 chasing1 the4 ball2 ., the numbers do not follow the natural reading order. Instead, they specify a shuffled sequence for a language modeling task, where the model might be trained to predict words based on this permuted arrangement rather than the standard left-to-right structure.
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Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Example of an Indexed Sentence with Non-Sequential Order
Example of a Sequentially Indexed Sentence
Example of a Permuted Sentence with Non-Sequential Indexing
Example of Permuted Language Modeling with a Shuffled Sentence
Consider two different training objectives for a language model. In Objective 1, the model learns by predicting a few randomly obscured words in a sentence, using all the other visible words as context. In Objective 2, the model is given a sentence's words in a randomly shuffled order and must predict them one by one according to that shuffled sequence, only using the words that have already appeared in that sequence as context. Which of the following statements best analyzes the key advantage of Objective 2?
A language model is trained using an objective where it predicts words from an input sentence one by one, but in a randomly shuffled order. For the sentence 'The quick brown fox', the model is given the prediction order [3, 1, 4, 2], corresponding to the original word positions. Arrange the following prediction tasks in the correct sequence that the model would perform.
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Encoding Process in Permuted Language Modeling
Example of Permuted Language Modeling
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A language model is being trained using a technique where the order of words to be predicted is shuffled. Given the input
A4 quick1 brown3 fox2 jumps5 ., what is the correct sequence for predicting the first four words?A language model is presented with the following input, where each word is paired with a number indicating its prediction order:
The5 quick2 brown4 fox1 jumps3 .. Arrange the words in the order they should be predicted by the model.A language model is processing an input where numbers dictate the prediction order:
The4 quick1 brown3 fox2 jumps5 .. When the model is about to predict the word corresponding to the number '3', what information from the sentence is available to it as context?