A development team aims to align a large language model with human preferences. Their methodology is as follows:

1. For each input prompt, generate 16 different responses from the model.
2. Use a pre-trained 'reward model' to assign a quality score to each of the 16 responses.
3. Select only the single highest-scoring response for that prompt.
4. Compile a new dataset consisting of thousands of these prompt-and-best-response pairs.
5. Fine-tune the original language model on this new dataset using standard supervised learning methods.

Which statement most accurately evaluates this team's approach?

Choosing an Alignment Strategy for a Startup

Comparing Model Alignment Techniques