Why is it better for an LLM judge to use pairwise comparisons or a small set of enums instead of numeric scores?
Numeric scoring turns judgment into a regression problem. LLMs are better at fuzzy semantic decisions than precise estimation: they have a lossy latent representation of the world, not a precisely calibrated one.
In general I would say LLMs excel at:
ranking > classification > regression