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Research at the intersection of personality psychology, computer science, and linguistics has recently focused increasingly on modeling and predicting personality from language use. We report two major improvements in predicting personality…

计算与语言 · 计算机科学 2022-04-12 Elma Kerz , Yu Qiao , Sourabh Zanwar , Daniel Wiechmann

This article analyzes the use of Large Language Models (LLMs) as support for the conceptual modeling of relational databases through the automatic generation of Entity-Relationship (ER) diagrams from natural language requirements. The…

We use generative agents powered by large language models (LLMs) to simulate a social network in a shared residential building, driving the temperature decisions for a central heating system. Agents, divided into Family Members and…

社会与信息网络 · 计算机科学 2025-07-15 Ann Nedime Nese Rende , Tolga Yilmaz , Özgür Ulusoy

Large language models (LLMs) have become increasingly proficient at simulating various personality traits, an important capability for supporting related applications (e.g., role-playing). To further improve this capacity, in this paper, we…

计算与语言 · 计算机科学 2024-10-17 Jia Deng , Tianyi Tang , Yanbin Yin , Wenhao Yang , Wayne Xin Zhao , Ji-Rong Wen

Behavioral parameters such as loss aversion, herding, and extrapolation are central to asset pricing models but remain difficult to measure reliably. We develop a framework that treats large language models (LLMs) as calibrated measurement…

综合经济学 · 经济学 2026-05-12 Brandon Yee , Pairie Koh

Associative learning--forming links between co-occurring items--is fundamental to human cognition, reshaping internal representations in complex ways. Testing hypotheses on how representational changes occur in biological systems is…

机器学习 · 计算机科学 2025-10-27 Camila Kolling , Vy Ai Vo , Mariya Toneva

This study seeks to uncover evidence of a latent structure in evolved human culture as it is refracted through contemporary large language models (LLMs). Drawing on parallel responses from six leading generative models to a prompt which…

计算机与社会 · 计算机科学 2026-04-09 W. Russell Neuman

This study proposes augmenting dialog data with think-aloud utterances (TAUs) for modeling individual personalities in text chat by LLM. TAU is a verbalization of a speaker's thought before articulating the utterance. We expect "persona…

计算与语言 · 计算机科学 2025-10-30 Seiya Ishikura , Hiroaki Yamada , Tatsuya Hiraoka , Hiroaki Yamada , Takenobu Tokunaga

As large language models (LLMs) increasingly participate in tasks with ethical and societal stakes, a critical question arises: do they exhibit an emergent "moral mind" - a consistent structure of moral preferences guiding their decisions -…

计算机与社会 · 计算机科学 2025-04-28 Avner Seror

Large Language Models (LLMs) represent a major step toward artificial general intelligence, significantly advancing our ability to interact with technology. While LLMs perform well on Natural Language Processing tasks -- such as…

计算与语言 · 计算机科学 2025-05-15 Brandon Smith , Mohamed Reda Bouadjenek , Tahsin Alamgir Kheya , Phillip Dawson , Sunil Aryal

The advancement of Large Language Models (LLMs) has led to their widespread use across a broad spectrum of tasks including decision making. Prior studies have compared the decision making abilities of LLMs with those of humans from a…

计算与语言 · 计算机科学 2024-01-01 Manikanta Loya , Divya Anand Sinha , Richard Futrell

Large language models (LLMs) are increasingly utilized to assist in scientific and academic writing, helping authors enhance the coherence of their articles. Previous studies have highlighted stereotypes and biases present in LLM outputs,…

计算与语言 · 计算机科学 2024-07-01 Naseela Pervez , Alexander J. Titus

This study analyzes changes in the attention mechanisms of large language models (LLMs) when used to understand natural conversations between humans (human-human). We analyze three use cases of LLMs: interactions over web content, code, and…

计算与语言 · 计算机科学 2024-03-11 Toshish Jawale , Chaitanya Animesh , Sekhar Vallath , Kartik Talamadupula , Larry Heck

Large language models (LLMs) are increasingly deployed to support human decision-making. This use of LLMs has concerning implications, especially when their prescriptions affect the welfare of others. To gauge how LLMs make social…

计算机与社会 · 计算机科学 2026-01-16 Saptarshi Pal , Abhishek Mallela , Christian Hilbe , Lenz Pracher , Chiyu Wei , Feng Fu , Santiago Schnell , Martin A Nowak

As Large Language Models (LLMs) increasingly integrate into everyday workflows, where users shape outcomes through multi-turn collaboration, a critical question emerges: do users with different personality traits systematically prefer…

计算与语言 · 计算机科学 2025-09-01 Sarfaroz Yunusov , Kaige Chen , Kazi Nishat Anwar , Ali Emami

Curiosity serves as a pivotal conduit for human beings to discover and learn new knowledge. Recent advancements of large language models (LLMs) in natural language processing have sparked discussions regarding whether these models possess…

计算与语言 · 计算机科学 2026-04-15 Haoyu Wang , Sihang Jiang , Yuyan Chen , Xiaojun Meng , Jiansheng Wei , Yitong Wang , Yanghua Xiao

The rapid advancements in large language models (LLMs) have significantly improved their ability to generate natural language, making texts generated by LLMs increasingly indistinguishable from human-written texts. Recent research has…

计算与语言 · 计算机科学 2024-12-05 Sergio E. Zanotto , Segun Aroyehun

Large language models (LLMs) exhibit expert-level performance in tasks across a wide range of different domains. Ethical issues raised by LLMs and the need to align future versions makes it important to know how state of the art models…

Large Language Models (LLMs) excel at producing broadly relevant text, but this generality becomes a limitation when user-specific preferences are required, such as recommending restaurants or planning travel. In these scenarios, users…

Smart home automation systems aim to improve the comfort and convenience of users in their living environment. However, adapting automation to user needs remains a challenge. Indeed, many systems still rely on hand-crafted routines for each…

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