[Submitted on 8 Oct 2026]
Title:The Social World Model Evaluation Gap
View a PDF of the paper titled The Social World Model Evaluation Gap, by Denglin Jiang (New York University) and 1 other authors
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Abstract:A negotiation assistant can reach a good deal without accurately predicting the other person's response. We ask whether evaluations of social world models test that prediction directly. We audit 113 works published from 1999 to 2026. 9 primary evaluations measure a real person's response to an action selected by the system or experimenter. Only 2 also compare an explicit response forecast with that response. Their predictors use information available when the action is chosen, and the evaluated responses were excluded from fitting; both randomize the intervention. A separate full-text check of 25 language-model works finds no experiment meeting these conditions. The other evaluations test current-state inference, task success, or prediction from recorded actions. We propose a 1-step negotiation experiment that separates these questions. The findings describe the audited sample, not the prevalence of this evaluation gap across the field.
Comments: Accepted at the NeurIPS 2026 Workshop on Foundation Models for Temporal Systems: From Forecasting to World Modeling (FMTS). 4 pages of main text plus references and appendix. Code and data: this https URL
Subjects:
Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2610.33014 [cs.CL]
(or arXiv:2610.33014v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2610.33014
arXiv-issued DOI via DataCite
Submission history
From: Denglin Jiang [view email] [v1] Thu, 8 Oct 2026 04:18:33 UTC (110 KB)
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