Aug 2026· Group Decision and Negotiation· Vol 35· 0 citations· 90 references
TL;DR
The results show that LLMs often mirror human-like mental accounting, including segregating gains and losses, treating nominally equivalent resources as non-fungible, and honoring sunk costs, although the strength and direction of these effects differ across models and conditions.
Large language models (LLMs) are used to simulate human participants in psychological research. We asked whether LLMs that reproduce human evaluations of a whistleblower's moral character also reproduce the motive attributions that accompany them. Five LLMs and two human samples (N = 125 and N = 742) evaluated a physic...
Evaluations of Large Language Models (LLMs) morality typically consider decisions in isolation, thus overlooking whether an individual's unrelated prior conduct influences the model's subsequent choices. This leaves open the question of whether, and to what extent, moral history shapes LLM decisional behaviors. Prior w...
When a language model answers a sequence of questions, researchers report the model and temperature but rarely what or how it was told about its own earlier answers. I show that this underreported setting behaves as a mode effect. Testing four large language model (LLM) families with revealed preference theory (GARP)...
Yick Chung· Sociological Methods & R...· 0 citations
Different capacities for mentalization across LLMs are demonstrated, and cognitive computational modeling is highlighted as a formal method for assessing comparative intelligence across humans and machines.
Aamir Sohail, Xintong Zhong, Arkady Konovalov et al.· 0 citations
A robust Political Compass Test evaluation framework is introduced that samples 300 configurations across an eight-dimensional perturbation space varying language, framing, instructions, answer format, option order, and persona wording, and results show most models lean Libertarian-Left on average and larger models sho...
Luka Debevc, Nishan Chatterjee, Antoine Doucet et al.· 0 citations
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