8 papers
Tracing Moral Foundations in Large Language Models
Chenxiao Yu, Bowen Yi, Farzan Karimi-Malekabadi +5
Large language models often produce human-like moral judgments, but it is unclear whether this reflects an internal conceptual structure or superficial ``moral mimicry.'' Using Mor…
The Moral Foundations Reddit Corpus
Jackson Trager, Alireza S. Ziabari, Elnaz Rahmati +15
Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, environmental action, political engagement, and protest. Various computational…
Theory Trace Card: Theory-Driven Socio-Cognitive Evaluation of LLMs
Farzan Karimi-Malekabadi, Suhaib Abdurahman, Zhivar Sourati +2
Socio-cognitive benchmarks for large language models (LLMs) often fail to predict real-world behavior, even when models achieve high benchmark scores. Prior work has attributed thi…
Realistic threat perception drives intergroup conflict: A causal, dynamic analysis using generative-agent simulations
Suhaib Abdurahman, Farzan Karimi-Malekabadi, Chenxiao Yu +2
Human conflict is often attributed to threats against material conditions and symbolic values, yet it remains unclear how they interact and which dominates. Progress is limited by…
Scaling Item-to-Standard Alignment with Large Language Models: Accuracy, Limits, and Solutions
Farzan Karimi-Malekabadi, Pooya Razavi, Sonya Powers
As educational systems evolve, ensuring that assessment items remain aligned with content standards is essential for maintaining fairness and instructional relevance. Traditional h…
Reasoning on a Spectrum: Aligning LLMs to System 1 and System 2 Thinking
Alireza S. Ziabari, Nona Ghazizadeh, Zhivar Sourati +3
Large Language Models (LLMs) exhibit impressive reasoning abilities, yet their reliance on structured step-by-step processing reveals a critical limitation. In contrast, human cogn…