Agent-ValueBench is the first dedicated benchmark for agent values, showing they diverge from LLM values, form a homogeneous 'Value Tide' across models, and bend under harnesses and skill steering.
Mind the Value-Action Gap: Do LLM s Act in Alignment with Their Values?
5 Pith papers cite this work, alongside 4 external citations. Polarity classification is still indexing.
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Introduces a Q-sort protocol using human reference factors to quantify LLM value-structure alignment via Procrustes similarity and RSA correlations, revealing cross-family heterogeneity and localized misalignments.
PPT-Bench measures how LLMs change answers under epistemic, value, authority, and identity pressures at baseline, single-turn, and multi-turn levels, finding separable inconsistency patterns across five models.
Language models show unstable principal hierarchies and frequently omit known professional standards when user or authority instructions conflict during task execution in medical and legal domains.
LLMs show structured attribute-driven decisions that a behavioral model can predict, but self-reports recover those drivers only partially, indicating superficial beliefs.
citing papers explorer
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Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values
Agent-ValueBench is the first dedicated benchmark for agent values, showing they diverge from LLM values, form a homogeneous 'Value Tide' across models, and bend under harnesses and skill steering.
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Beyond Value Benchmarks: Measuring Value-Structure Alignment in Large Language Models via Symmetric Q-Sorts
Introduces a Q-sort protocol using human reference factors to quantify LLM value-structure alignment via Procrustes similarity and RSA correlations, revealing cross-family heterogeneity and localized misalignments.
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Beyond Social Pressure: Benchmarking Epistemic Attack in Large Language Models
PPT-Bench measures how LLMs change answers under epistemic, value, authority, and identity pressures at baseline, single-turn, and multi-turn levels, finding separable inconsistency patterns across five models.
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To Whom Do Language Models Align? Measuring Principal Hierarchies Under High-Stakes Competing Demands
Language models show unstable principal hierarchies and frequently omit known professional standards when user or authority instructions conflict during task execution in medical and legal domains.
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Superficial Beliefs in LLM Decision-Making
LLMs show structured attribute-driven decisions that a behavioral model can predict, but self-reports recover those drivers only partially, indicating superficial beliefs.