Formulating Conditional Probability in Dialogue
A dialogue model is engaged in a conversation that has reached its third turn. The full history of the conversation so far is {x_1, y_1, x_2, y_2, x_3}, where x_k is the user's input and y_k is the model's response at turn k. Write the mathematical expression for the conditional log-probability that the model uses to generate its next response, y_3.
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Ch.4 Alignment - 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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Training Objective for Multi-Round Dialogue Models
Consider a dialogue model engaged in a three-turn conversation, represented by the sequence
{x_1, y_1, x_2, y_2, x_3, y_3}, wherex_kis the user's input andy_kis the model's response at turnk. When the model calculates the probability of generating the third response (y_3), how does the set of information it conditions on relate to the set of information used to calculate the probability of the second response (y_2)?Formulating Conditional Probability in Dialogue
Diagnosing Conversational Memory Failure