Learn Before
A language model is given an input sequence of tokens representing the phrase 'The best way to learn a new skill is'. The model then calculates the likelihood for several possible completing sequences. Based on the formal objective of the text generation process, which of the following sequences should the model select to output?
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Ch.5 Inference - Foundations of Large Language Models
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
Mathematical Formulation of LLM Inference
Single-Round Prediction Problem
Token-Level Representation of Input and Output Sequences for a Forward Pass
Multi-Round Prediction Problem
Notation for Concatenated Token Sequences
A language model is given an input sequence of tokens representing the phrase 'The best way to learn a new skill is'. The model then calculates the likelihood for several possible completing sequences. Based on the formal objective of the text generation process, which of the following sequences should the model select to output?
Analyzing Model Output Selection
A language model is given an input context
x. It then evaluates two potential output sequences,y_1andy_2. The model's internal calculations determine thaty_1has a higher probability of occurring afterxthany_2. However, a human evaluator findsy_2to be more creative and detailed. According to the formal objective of the text generation process, what should the model do?