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In a language model that uses separate vectors for token identity, position, and sentence membership, the final input vector for a token is created by concatenating these three component vectors end-to-end.
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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
Comprehension in Revised Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
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A researcher is debugging a language model where the input representation for each token is created by summing three distinct vectors: one for the token's identity, one for its position in the sequence, and one for the sentence segment it belongs to. The researcher observes that the model treats the sentences 'The scientist observed the star' and 'The star observed the scientist' as having identical meanings. Which of the three component vectors is most likely being calculated incorrectly or omi
Debugging Sentence Pair Representations
Segment Embedding
Example of Input Embedding Composition for a Sentence Pair