Social Choice Foundations for Simulation-Augmented Generation
Simulation-augmented generation (SAGE) is a recent technical proposal in which models simulate individuals' viewpoints at inference time in order to provide more representative answers to contentious user queries. A core challenge for SAGE is making inference-time simulation efficient without sacrificing representation quality. We introduce the first formalization of this problem, based upon an axiom from proportional clustering known as metric proportional justified representation+ (mPJR+) which is the strongest proportionality axiom known to always be satisfiable by centroid-based clustering. We prove that to proportionally represent the viewpoints of a population of $n_H$ humans on a g...
| Authors | Sonja Kraiczy, Smitha Milli, Ratip Emin Berker et al. |
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| Primary category | cs.GT |
| Published | 29 September 2026 |
| Last updated at source | 29 September 2026 |
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