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While both agent interaction and personalisation are vibrant topics in research on large language models (LLMs), there has been limited focus on the effect of language interaction on the behaviour of persona-conditioned LLM agents. Such an…

Computation and Language · Computer Science 2024-02-06 Ivar Frisch , Mario Giulianelli

The proliferation of wearable technology enables the generation of vast amounts of sensor data, offering significant opportunities for advancements in health monitoring, activity recognition, and personalized medicine. However, the…

Human-Computer Interaction · Computer Science 2024-08-02 Emilio Ferrara

Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across society. This dissertation examines how individuals and institutions are adapting to and…

Computation and Language · Computer Science 2025-06-24 Weixin Liang

Large language models (LLMs) have demonstrated their potential in social science research by emulating human perceptions and behaviors, a concept referred to as algorithmic fidelity. This study assesses the algorithmic fidelity and bias of…

Artificial Intelligence · Computer Science 2024-08-09 S. Lee , T. Q. Peng , M. H. Goldberg , S. A. Rosenthal , J. E. Kotcher , E. W. Maibach , A. Leiserowitz

Large language models (LLMs) are trained on vast amounts of data to generate natural language, enabling them to perform tasks like text summarization and question answering. These models have become popular in artificial intelligence (AI)…

We explore the potential of Large Language Models (LLMs) to replicate human behavior in economic market experiments. Compared to previous studies, we focus on dynamic feedback between LLM agents: the decisions of each LLM impact the market…

General Economics · Economics 2025-05-13 R. Maria del Rio-Chanona , Marco Pangallo , Cars Hommes

The emergence of Large Language Models (LLMs) have fundamentally altered the way we interact with digital systems and have led to the pursuit of LLM powered AI agents to assist in daily workflows. LLMs, whilst powerful and capable of…

Computation and Language · Computer Science 2024-08-05 Prattyush Mangal , Carol Mak , Theo Kanakis , Timothy Donovan , Dave Braines , Edward Pyzer-Knapp

The advancement of generative AI, particularly large language models (LLMs), has a significant impact on politics and democracy, offering potential across various domains, including policymaking, political communication, analysis, and…

Computation and Language · Computer Science 2024-12-17 Goshi Aoki

The era of Large Language Models (LLMs) presents a new opportunity for interpretability--agentic interpretability: a multi-turn conversation with an LLM wherein the LLM proactively assists human understanding by developing and leveraging a…

Artificial Intelligence · Computer Science 2025-06-17 Been Kim , John Hewitt , Neel Nanda , Noah Fiedel , Oyvind Tafjord

Social network simulation plays a crucial role in addressing various challenges within social science. It offers extensive applications such as state prediction, phenomena explanation, and policy-making support, among others. In this work,…

Social and Information Networks · Computer Science 2025-06-05 Chen Gao , Xiaochong Lan , Zhihong Lu , Jinzhu Mao , Jinghua Piao , Huandong Wang , Depeng Jin , Yong Li

Cutting-edge Artificial Intelligence (AI) techniques keep reshaping our view of the world. For example, Large Language Models (LLMs) based applications such as ChatGPT have shown the capability of generating human-like conversation on…

Contemporary artificial intelligence research has been organized around two dominant ambitions: productivity, which treats AI systems as tools for accelerating work and economic output, and alignment, which focuses on ensuring that…

Artificial Intelligence · Computer Science 2026-03-10 W. Russell Neuman , Chad Coleman

Agent-based modeling (ABM) is a well-established paradigm for simulating complex systems via interactions between constituent entities. Machine learning (ML) refers to approaches whereby statistical algorithms 'learn' from data on their…

Quantitative Methods · Quantitative Biology 2022-11-10 Nikita Sivakumar , Cameron Mura , Shayn M. Peirce

Agent-based modeling and simulation has evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. Integrating large language models into agent-based modeling…

Artificial Intelligence · Computer Science 2023-12-20 Chen Gao , Xiaochong Lan , Nian Li , Yuan Yuan , Jingtao Ding , Zhilun Zhou , Fengli Xu , Yong Li

Large language model (LLM)-based multi-agent systems enable expressive agent reasoning but are expensive to scale and poorly calibrated for timestep-aligned state-transition simulation, while classical agent-based models (ABMs) offer…

Multiagent Systems · Computer Science 2026-02-10 Kavana Venkatesh , Yinhan He , Jundong Li , Jiaming Cui

The long-standing vision of intelligent cities is to create efficient, livable, and sustainable urban environments using big data and artificial intelligence technologies. Recently, the advent of Large Language Models (LLMs) has opened new…

Multiagent Systems · Computer Science 2025-07-02 Jindong Han , Yansong Ning , Zirui Yuan , Hang Ni , Fan Liu , Tengfei Lyu , Hao Liu

Accurate prediction of human behavior is crucial for AI systems to effectively support real-world applications, such as autonomous robots anticipating and assisting with human tasks. Real-world scenarios frequently present challenges such…

Human-Computer Interaction · Computer Science 2025-07-21 Kojiro Takeyama , Yimeng Liu , Misha Sra

Large language models (LLMs) are powerful artificial intelligence (AI) tools transforming how research is conducted. However, their use in research has been met with skepticism, due to concerns about hallucinations, biases and potential…

Artificial Intelligence · Computer Science 2025-07-08 Ruian Ke , Ruy M. Ribeiro

With the rapid development of large language models (LLMs), it is highly demanded that LLMs can be adopted to make decisions to enable the artificial general intelligence. Most approaches leverage manually crafted examples to prompt the…

Machine Learning · Computer Science 2023-12-15 Xingjin Wang , Linjing Li , Daniel Zeng

Intelligent agents stand out as a potential path toward artificial general intelligence (AGI). Thus, researchers have dedicated significant effort to diverse implementations for them. Benefiting from recent progress in large language models…

Artificial Intelligence · Computer Science 2024-01-09 Yuheng Cheng , Ceyao Zhang , Zhengwen Zhang , Xiangrui Meng , Sirui Hong , Wenhao Li , Zihao Wang , Zekai Wang , Feng Yin , Junhua Zhao , Xiuqiang He