arXiv cs.LG
· Papers
From Weights to Words: Expressing and Editing Preference Model Inferences in Natural Language
arXiv:2607.16232v1 Announce Type: new Abstract: The growing use of statistical learning algorithms to infer human preferences from high-dimensional choice data runs up against a fundamental challenge: choice alternatives typically differ in many ways simultaneously, so it is generally unclear which factors actually dro