arXiv — NLP / Computation & Language · · 3 min read

Every Act Has Its Price: Compressed Moral Composition in Frontier LLMs

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Computer Science > Computation and Language

arXiv:2606.11232 (cs)
[Submitted on 29 May 2026]

Title:Every Act Has Its Price: Compressed Moral Composition in Frontier LLMs

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Abstract:Existing LLM moral benchmarks usually ask which isolated moral act, value, or foundation a model prefers. This is useful but incomplete. Realistic judgments often require a model to combine several moral signals within the same option. We introduce **Moral Trolley Arena**, a two-stage blind ELO benchmark for measuring how LLMs compose moral evidence. The single-scene arena first calibrates individual moral acts from a 229-scenario corpus across five Moral Foundations Theory foundations; the composite arena then combines calibrated acts into two-act moral items over a controlled intensity grid and measures the resulting composite preferences. Across ten frontier models, composite judgments are largely predicted by component act strength, but the relation is consistently compressed rather than simply additive. Models also show non-additive intensity anchoring, bounded foundation-specific residuals after component control, and highly convergent composite preference surfaces across providers. These results suggest that moral audits should measure composition rules for moral evidence, not only rankings over isolated acts.
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2606.11232 [cs.CL]
  (or arXiv:2606.11232v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2606.11232
arXiv-issued DOI via DataCite

Submission history

From: Weijia Zhang [view email]
[v1] Fri, 29 May 2026 02:36:10 UTC (1,191 KB)
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