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Analyzing the Span Prediction Constraint
A language model has generated start and end log-probabilities for a 5-token sequence. The highest start log-probability is for token 4, and the highest end log-probability is for token 2. If one were to naively select the span based on these two independent maximums, the resulting span would be invalid. Explain why this span is invalid and how the standard span prediction formula, , prevents this specific issue.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
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A language model is tasked with finding an answer span within a text. After processing the text, it produces the following log-probabilities for each token being the start or the end of the answer. To find the best span, one must find the start index () and end index () that maximize the sum of their log-probabilities, with the constraint that the start index cannot be after the end index ().
Index Token Start Log-Prob End Log-Prob 1 The -5.1 -8.1 2 first -4.2 -7.2 3 person -4.5 -6.5 4 was -5.5 -5.5 5 Neil -0.9 -3.1 6 Armstrong -2.1 -0.5 Given the table above, what is the predicted answer span?
Analyzing the Span Prediction Constraint
Diagnosing a Span Prediction Error