A language model is generating a sequence of tokens. The total log-probability for the partially generated sequence 'The quick brown' has been calculated as -3.5. In the very next step, the model computes the conditional log-probability for the token 'fox' as -1.2. What is the new total log-probability for the complete sequence 'The quick brown fox'?
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Ch.5 Inference - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
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Greedy Search (Greedy Decoding)
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A language model is generating a sequence of tokens. The total log-probability for the partially generated sequence 'The quick brown' has been calculated as -3.5. In the very next step, the model computes the conditional log-probability for the token 'fox' as -1.2. What is the new total log-probability for the complete sequence 'The quick brown fox'?
A language model is generating a sequence. The table below shows the conditional log-probability for each new token and the claimed total accumulated log-probability for the sequence up to that point. Analyze the table to identify the first step where the total accumulated log-probability is calculated incorrectly based on the principle of incremental summation.
Step Token Conditional log-prob Total Accumulated log-prob 1 'The' -0.9 -0.9 2 'cat' -1.5 -2.4 3 'sat' -1.1 -2.6 Comparing Generation Paths