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GUIs have long been central to human-computer interaction, providing an intuitive and visually-driven way to access and interact with digital systems. The advent of LLMs, particularly multimodal models, has ushered in a new era of GUI…

Graphical User Interface (GUI) Agents have emerged as a transformative paradigm in human-computer interaction, evolving from rule-based automation scripts to sophisticated AI-driven systems capable of understanding and executing complex…

Recent advancements in Large Language Models (LLMs) have led to the development of intelligent LLM-based agents capable of interacting with graphical user interfaces (GUIs). These agents demonstrate strong reasoning and adaptability,…

人工智能 · 计算机科学 2025-04-16 Wenjia Jiang , Yangyang Zhuang , Chenxi Song , Xu Yang , Joey Tianyi Zhou , Chi Zhang

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

Recent advances in foundation models, particularly Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs), have facilitated the development of intelligent agents capable of performing complex tasks. By leveraging the…

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…

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…

Large language models (LLMs) have evolved beyond simple text generation to power software agents that directly translate natural language commands into tangible actions. While API-based LLM agents initially rose to prominence for their…

人工智能 · 计算机科学 2025-06-24 Chaoyun Zhang , Shilin He , Liqun Li , Si Qin , Yu Kang , Qingwei Lin , Saravan Rajmohan , Dongmei Zhang

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

Graphical User Interface (GUI) agents, driven by Multi-modal Large Language Models (MLLMs), have emerged as a promising paradigm for enabling intelligent interaction with digital systems. This paper provides a structured survey of recent…

人工智能 · 计算机科学 2025-05-14 Jiahao Li , Kaer Huang

The evolution of Large Language Models (LLMs) from passive text generators to autonomous, goal-driven systems represents a fundamental shift in artificial intelligence. This chapter examines the emergence of agentic AI systems that…

人工智能 · 计算机科学 2026-01-07 Nadia Sibai , Yara Ahmed , Serry Sibaee , Sawsan AlHalawani , Adel Ammar , Wadii Boulila

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

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…

Large Language Model (LLM) agents are transforming education by automating complex pedagogical tasks and enhancing both teaching and learning processes. In this survey, we present a systematic review of recent advances in applying LLM…

计算机与社会 · 计算机科学 2026-02-05 Zhendong Chu , Shen Wang , Jian Xie , Tinghui Zhu , Yibo Yan , Jinheng Ye , Aoxiao Zhong , Xuming Hu , Jing Liang , Philip S. Yu , Qingsong Wen

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

With the rise of large language models (LLMs), researchers are increasingly exploring their applications in var ious vertical domains, such as software engineering. LLMs have achieved remarkable success in areas including code generation…

软件工程 · 计算机科学 2025-04-15 Haolin Jin , Linghan Huang , Haipeng Cai , Jun Yan , Bo Li , Huaming Chen

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) have precipitated a dramatic improvement in the legal domain, yet the deployment of standalone models faces significant limitations regarding hallucination, outdated information, and verifiability. Recently, LLM…

计算机与社会 · 计算机科学 2026-01-13 Shuang Liu , Ruijia Zhang , Ruoyun Ma , Yujia Deng , Lanyi Zhu , Jiayu Li , Zelong Li , Zhibin Shen , Mengnan Du

Mobile agents are essential for automating tasks in complex and dynamic mobile environments. As foundation models evolve, the demands for agents that can adapt in real-time and process multimodal data have grown. This survey provides a…

人工智能 · 计算机科学 2025-09-16 Biao Wu , Yanda Li , Zhiwei Zhang , Yunchao Wei , Meng Fang , Ling Chen

For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are artificial entities that sense their environment,…

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