Analyzing Model Output Probability
A developer is testing a translation model. The model is given the instruction, 'Translate the following English sentence to French,' and the input, 'The cat is on the mat.' The model considers two possible outputs: (y1) 'Le chat est sur le tapis' and (y2) 'Le tapis est sur le chat.' Using the formal representation Pr(y|c, z), explain how the model computationally distinguishes between these two outputs and determines the more appropriate translation.
0
1
Tags
Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
A user interacts with a language model by providing an instruction and an input. The instruction is 'Summarize the key point of the following text.' The input text is 'Jupiter is the fifth planet from the Sun and the largest in the Solar System.' The model generates the output 'Jupiter is the largest planet in our solar system.' How is the conditional probability of the model generating this specific output formally represented?
An instruction-tuned model's behavior can be formally represented as a conditional probability distribution
Pr(y|c, z). Match each variable from this representation to its corresponding description.Analyzing Model Output Probability