A development team is using a four-stage process to align a language model with human preferences. They collect a large dataset where human annotators consistently rank verbose and evasive responses as low quality. This dataset is then used to train a reward model. Finally, the language model is fine-tuned using reinforcement learning, with the reward model providing the optimization signal. However, the final, aligned language model still frequently produces verbose and evasive outputs. Which stage is the most likely source of this failure?
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
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A team is developing a language model designed to align with human preferences. They are following a standard four-stage process. Arrange the following stages in the correct chronological order.
A development team is using a four-stage process to align a language model with human preferences. They collect a large dataset where human annotators consistently rank verbose and evasive responses as low quality. This dataset is then used to train a reward model. Finally, the language model is fine-tuned using reinforcement learning, with the reward model providing the optimization signal. However, the final, aligned language model still frequently produces verbose and evasive outputs. Which stage is the most likely source of this failure?
A team is aligning a language model with human preferences using a four-stage process. Match each stage of the process to its primary function and the key artifact it produces.