Reward Score Formula for LLM-based Reward Models

End-of-Sequence Reward Assignment in RLHF

In a system designed to evaluate the quality of generated text, a complex neural network first processes a prompt and its corresponding response, ultimately producing a high-dimensional vector that captures the nuanced meaning and relationship between them. What is the essential final step required to convert this complex vector into a practical, usable evaluation, and what is the nature of its output?

Troubleshooting a Reward Model's Output

From Representation to Reward