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The pursuit of human-level artificial intelligence (AI) has significantly advanced the development of autonomous agents and Large Language Models (LLMs). LLMs are now widely utilized as decision-making agents for their ability to interpret…

This paper reviews the architecture and implementation methods of agents powered by large language models (LLMs). Motivated by the limitations of traditional LLMs in real-world tasks, the research aims to explore patterns to develop…

人工智能 · 计算机科学 2025-10-13 Victor de Lamo Castrillo , Habtom Kahsay Gidey , Alexander Lenz , Alois Knoll

Large Language Models (LLMs) are transforming artificial intelligence, enabling autonomous agents to perform diverse tasks across various domains. These agents, proficient in human-like text comprehension and generation, have the potential…

人工智能 · 计算机科学 2024-04-10 Saikat Barua

Large language models (LLMs) process and predict sequences containing text to answer questions, and address tasks including document summarization, providing recommendations, writing software and solving quantitative problems. We provide a…

数值分析 · 数学 2026-02-02 Ricardo Baptista , Andrew Stuart , Son Tran

The rapid advancement of Large Language Models (LLMs) has driven novel applications across diverse domains, with LLM-based agents emerging as a crucial area of exploration. This survey presents a comprehensive analysis of LLM-based agents…

人工智能 · 计算机科学 2025-11-25 Ke Chen , Peiran Wang , Yaoning Yu , Xianyang Zhan , Haohan Wang

Large language models (LLMs) are a class of artificial intelligence models based on deep learning, which have great performance in various tasks, especially in natural language processing (NLP). Large language models typically consist of…

定量方法 · 定量生物学 2025-02-04 Jiajia Liu , Mengyuan Yang , Yankai Yu , Haixia Xu , Tiangang Wang , Kang Li , Xiaobo Zhou

As the strength of Large Language Models (LLMs) has grown over recent years, so too has interest in their use as the underlying models for autonomous agents. Although LLMs demonstrate emergent abilities and broad expertise across natural…

人工智能 · 计算机科学 2024-12-06 Chris Sypherd , Vaishak Belle

The emergence of Large Language Models (LLMs) with increasingly sophisticated natural language understanding and generative capabilities has sparked interest in the Agent-based Modelling (ABM) community. With their ability to summarize,…

Simulations, although powerful in accurately replicating real-world systems, often remain inaccessible to non-technical users due to their complexity. Conversely, large language models (LLMs) provide intuitive, language-based interactions…

计算与语言 · 计算机科学 2025-05-22 Jacob Kleiman , Kevin Frank , Joseph Voyles , Sindy Campagna

In recent years, data science agents powered by Large Language Models (LLMs), known as "data agents," have shown significant potential to transform the traditional data analysis paradigm. This survey provides an overview of the evolution,…

人工智能 · 计算机科学 2025-12-01 Maojun Sun , Ruijian Han , Binyan Jiang , Houduo Qi , Defeng Sun , Yancheng Yuan , Jian Huang

The era of intelligent agents is upon us, driven by revolutionary advancements in large language models. Large Language Model (LLM) agents, with goal-driven behaviors and dynamic adaptation capabilities, potentially represent a critical…

The emergence of Large Language Models (LLMs) has reshaped agent systems. Unlike traditional rule-based agents with limited task scope, LLM-powered agents offer greater flexibility, cross-domain reasoning, and natural language interaction.…

人工智能 · 计算机科学 2026-05-05 Guannan Liang , Qianqian Tong

Large language models (LLMs) enable researchers to analyze text at unprecedented scale and minimal cost. Researchers can now revisit old questions and tackle novel ones with rich data. We provide an econometric framework for realizing this…

计量经济学 · 经济学 2025-12-08 Jens Ludwig , Sendhil Mullainathan , Ashesh Rambachan

Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used as autonomous agents to do many tasks automatically. Recently,…

计算与语言 · 计算机科学 2024-04-22 Taicheng Guo , Xiuying Chen , Yaqi Wang , Ruidi Chang , Shichao Pei , Nitesh V. Chawla , Olaf Wiest , Xiangliang Zhang

Recommender systems are essential components of many online platforms, yet traditional approaches still struggle with understanding complex user preferences and providing explainable recommendations. The emergence of Large Language Model…

信息检索 · 计算机科学 2025-03-05 Qiyao Peng , Hongtao Liu , Hua Huang , Qing Yang , Minglai Shao

Large Language Models (LLMs) have emerged as powerful tools in various research domains. This article examines their potential through a literature review and firsthand experimentation. While LLMs offer benefits like cost-effectiveness and…

人机交互 · 计算机科学 2024-04-10 M. Namvarpour , A. Razi

The recent advance in Large Language Models (LLMs) has shaped a new paradigm of AI agents, i.e., LLM-based agents. Compared to standalone LLMs, LLM-based agents substantially extend the versatility and expertise of LLMs by enhancing LLMs…

软件工程 · 计算机科学 2025-12-04 Junwei Liu , Kaixin Wang , Yixuan Chen , Xin Peng , Zhenpeng Chen , Lingming Zhang , Yiling Lou

Large language models (LLMs) and agent techniques have brought a fundamental shift in the functionality and development paradigm of data analysis tasks (a.k.a LLM/Agent-as-Data-Analyst), demonstrating substantial impact across both academia…

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…

人工智能 · 计算机科学 2025-06-17 Been Kim , John Hewitt , Neel Nanda , Noah Fiedel , Oyvind Tafjord

This paper surveys the development of large language model (LLM)-based agents for question answering (QA). Traditional agents face significant limitations, including substantial data requirements and difficulty in generalizing to new…

计算与语言 · 计算机科学 2025-03-26 Murong Yue
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