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Large Language Models (LLMs) such as OpenAI's GPT-4 and Meta's LLaMA offer a promising approach for scalable personality assessment from open-ended language. However, inferring personality traits remains challenging, and earlier work often…

Computation and Language · Computer Science 2025-07-22 Jianfeng Zhu , Ruoming Jin , Karin G. Coifman

While LLM agents have demonstrated remarkable task-oriented abilities such as planning, reasoning, and action, few works have treated them as complete human personalities where emotional dimensions hold equal importance. In this paper, we…

Computation and Language · Computer Science 2026-05-29 Weihan Peng , Chenxu Zhang , Qianao Wang , Yuling Shi , Heng Lian , Qihong Mao , Jiahao Pang , Chunliang Feng , Bowen Li , Xiaodong Gu

Reward models (RMs) are essential for aligning large language models (LLMs) with human preferences to improve interaction quality. However, the real world is pluralistic, which leads to diversified human preferences with respect to…

Computation and Language · Computer Science 2023-09-18 Pengyu Cheng , Jiawen Xie , Ke Bai , Yong Dai , Nan Du

In recent years, large language models (LLMs) have attracted attention due to their ability to generate human-like text. As surveys and opinion polls remain key tools for gauging public attitudes, there is increasing interest in assessing…

General Economics · Economics 2025-02-12 Shapeng Jiang , Lijia Wei , Chen Zhang

Recent advancements in Large Language Models (LLMs) have led to their adaptation in various domains as conversational agents. We wonder: can personality tests be applied to these agents to analyze their behavior, similar to humans? We…

This study investigates the efficacy of large language models (LLMs) as tools for grading master-level student essays. Utilizing a sample of 60 essays in political science, the study compares the accuracy of grades suggested by the GPT-4…

General Economics · Economics 2024-06-25 Magnus Lundgren

Improving the multi-step reasoning ability of Large Language Models (LLMs) is a critical yet challenging task. The dominant paradigm, outcome-supervised reinforcement learning (RLVR), rewards only correct final answers, often propagating…

Artificial Intelligence · Computer Science 2025-10-14 Beining Wang , Weihang Su , Hongtao Tian , Tao Yang , Yujia Zhou , Ting Yao , Qingyao Ai , Yiqun Liu

As large language models (LLM) evolve in their capabilities, various recent studies have tried to quantify their behavior using psychological tools created to study human behavior. One such example is the measurement of "personality" of…

Computation and Language · Computer Science 2024-01-04 Akshat Gupta , Xiaoyang Song , Gopala Anumanchipalli

Large language models (LLMs) are recognized as systems that closely mimic aspects of human intelligence. This capability has attracted attention from the social science community, who see the potential in leveraging LLMs to replace human…

Computers and Society · Computer Science 2025-03-04 Qiuejie Xie , Qiming Feng , Tianqi Zhang , Qingqiu Li , Linyi Yang , Yuejie Zhang , Rui Feng , Liang He , Shang Gao , Yue Zhang

Personality detection aims to measure an individual's corresponding personality traits through their social media posts. The advancements in Large Language Models (LLMs) offer novel perspectives for personality detection tasks. Existing…

Computation and Language · Computer Science 2026-01-27 Yuan Cao , Feixiang Liu , Xinyue Wang , Yihan Zhu , Hui Xu , Zheng Wang , Qiang Qiu

Large language models (LLMs) are increasingly used in clinical and care settings. This exploratory study investigates whether LLMs exhibit sycophantic behavior - adapting their responses to social expectation signals rather than maintaining…

Computers and Society · Computer Science 2026-05-19 Christian Kolb

Large Language Models (LLMs), though shown to be effective in many applications, can vary significantly in their response quality. In this paper, we investigate this problem of prompt fairness: specifically, the phrasing of a prompt by…

Machine Learning · Computer Science 2025-11-26 Meiyu Zhong , Noel Teku , Ravi Tandon

Deep Research agents driven by LLMs have automated the scholarly discovery pipeline, from planning and query formulation to iterative web exploration. Yet they remain constrained by a static, ``one-size-fits-all'' retrieval paradigm.…

Information Retrieval · Computer Science 2026-05-12 Xiaopeng Li , Wenlin Zhang , Yingyi Zhang , Pengyue Jia , Yejing Wang , Yichao Wang , Yong Liu , Huifeng Guo , Xiangyu Zhao

Large language models (LLMs) are increasingly used as proxies for human judgment in computational social science, yet their ability to reproduce patterns of susceptibility to misinformation remains unclear. We test whether LLM-simulated…

Social and Information Networks · Computer Science 2026-04-13 Eun Cheol Choi , Lindsay E. Young , Emilio Ferrara

Despite their global prevalence, many Large Language Models (LLMs) are aligned to a monolithic, often Western-centric set of values. This paper investigates the more challenging task of fine-grained value alignment: examining whether LLMs…

Computers and Society · Computer Science 2026-04-15 Bryan Chen Zhengyu Tan , Zhengyuan Liu , Xiaoyuan Yi , Jing Yao , Xing Xie , Nancy F. Chen , Roy Ka-Wei Lee

This paper investigates Large Language Models (LLMs) ability to assess the economic soundness and theoretical consistency of empirical findings in spatial econometrics. We created original and deliberately altered "counterfactual" summaries…

Computers and Society · Computer Science 2025-06-10 Giuseppe Arbia , Luca Morandini , Vincenzo Nardelli

Verifiers or reward models are often used to enhance the reasoning performance of large language models (LLMs). A common approach is the Best-of-N method, where N candidate solutions generated by the LLM are ranked by a verifier, and the…

Machine Learning · Computer Science 2025-02-25 Lunjun Zhang , Arian Hosseini , Hritik Bansal , Mehran Kazemi , Aviral Kumar , Rishabh Agarwal

Large language models (LLMs) are increasingly used in social science as scalable measurement tools for converting unstructured text into variables that can enter standard empirical designs. Measurement validity demands more than high…

Artificial Intelligence · Computer Science 2026-05-13 Jinyuan Wang , Ningyuan Deng , Yi Yang

A Large Language Model (LLM) is an artificial intelligence system that has been trained on vast amounts of natural language data, enabling it to generate human-like responses to written or spoken language input. GPT-3.5 is an example of an…

Artificial Intelligence · Computer Science 2023-05-09 Gaurav Suri , Lily R. Slater , Ali Ziaee , Morgan Nguyen

As large language models (LLMs) are deployed in consequential settings such as medical question answering and legal reasoning, the ability to estimate when their outputs are likely to be correct is essential for safe and reliable use,…

Computation and Language · Computer Science 2026-05-22 Fengfei Yu , Ruijia Niu , Dongxia Wu , Yian Ma , Rose Yu