A team is developing a chatbot for multi-turn conversations. They have a dataset of K-round dialogues, each consisting of a sequence of user inputs (x^k) and desired model responses (y^k). To train the model, they must define an objective function that the model's parameters will be optimized to maximize. Which of the following objective functions correctly represents the goal of making the model generate the entire sequence of desired responses accurately within the conversational context?
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
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Comparison of Training Implementations for Multi-Round Dialogue Models
A team is developing a chatbot for multi-turn conversations. They have a dataset of K-round dialogues, each consisting of a sequence of user inputs (x^k) and desired model responses (y^k). To train the model, they must define an objective function that the model's parameters will be optimized to maximize. Which of the following objective functions correctly represents the goal of making the model generate the entire sequence of desired responses accurately within the conversational context?
Diagnosing Context-Loss in a Dialogue Model
Rationale for Cumulative Objective in Dialogue Models
Dataset-Level Objective for Multi-Round Conversational Models