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相关论文: Enhancing Trust in LLM-Based AI Automation Agents:…

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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) have shown surprising proficiency in generating code snippets, promising to automate large parts of software engineering via artificial intelligence (AI). We argue that successfully deploying AI software…

软件工程 · 计算机科学 2025-09-24 Abhik Roychoudhury , Corina Pasareanu , Michael Pradel , Baishakhi Ray

The rise of LLM-based agents has opened new frontiers in AI applications, yet evaluating these agents remains a complex and underdeveloped area. This survey provides an in-depth overview of the emerging field of LLM agent evaluation,…

机器学习 · 计算机科学 2025-07-30 Mahmoud Mohammadi , Yipeng Li , Jane Lo , Wendy Yip

Agentic AI systems powered by large language models (LLMs) and endowed with planning, tool use, memory, and autonomy, are emerging as powerful, flexible platforms for automation. Their ability to autonomously execute tasks across web,…

人工智能 · 计算机科学 2026-04-07 Anshuman Chhabra , Shrestha Datta , Shahriar Kabir Nahin , Prasant Mohapatra

AI-based systems, including Large Language Models (LLM), impact millions by supporting diverse tasks but face issues like misinformation, bias, and misuse. AI ethics is crucial as new technologies and concerns emerge, but objective,…

计算机与社会 · 计算机科学 2025-05-19 José Antonio Siqueira de Cerqueira , Mamia Agbese , Rebekah Rousi , Nannan Xi , Juho Hamari , Pekka Abrahamsson

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,…

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

Agentic AI systems -- Large Language Models (LLMs) augmented with planning, tool use, memory, and long-horizon interactions -- can execute complex tasks autonomously, but their multi-step trajectories introduce new failure modes that…

As AI agents built on large language models (LLMs) become increasingly embedded in society, issues of coordination, control, delegation, and accountability are entangled with concerns over their reliability. To design and implement LLM…

计算机与社会 · 计算机科学 2025-12-09 R. Patrick Xian , Garry A. Gabison , Ahmed Alaa , Christoph Riedl , Grigorios G. Chrysos

LLM-based agents represent a paradigm shift in AI, enabling autonomous systems to plan, reason, and use tools while interacting with dynamic environments. This paper provides the first comprehensive survey of evaluation methods for these…

人工智能 · 计算机科学 2026-04-24 Asaf Yehudai , Lilach Eden , Alan Li , Guy Uziel , Yilun Zhao , Roy Bar-Haim , Arman Cohan , Michal Shmueli-Scheuer

With the rise of large language models (LLMs), LLM agents capable of autonomous reasoning, planning, and executing complex tasks have become a frontier in artificial intelligence. However, how to translate the research on general agents…

The rapid progress in Large Language Models (LLMs) could transform many fields, but their fast development creates significant challenges for oversight, ethical creation, and building user trust. This comprehensive review looks at key trust…

计算机与社会 · 计算机科学 2024-07-22 Md Meftahul Ferdaus , Mahdi Abdelguerfi , Elias Ioup , Kendall N. Niles , Ken Pathak , Steven Sloan

AI agents are autonomous systems designed to perceive, reason, and act within dynamic environments. With the rapid advancements in generative AI (GenAI), large language models (LLMs) and multimodal large language models (MLLMs) have…

人工智能 · 计算机科学 2025-07-03 Yinwang Ren , Yangyang Liu , Tang Ji , Xun Xu

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

The past few decades have witnessed an upsurge in data, forming the foundation for data-hungry, learning-based AI technology. Conversational agents, often referred to as AI chatbots, rely heavily on such data to train large language models…

计算与语言 · 计算机科学 2024-11-19 Sumit Kumar Dam , Choong Seon Hong , Yu Qiao , Chaoning Zhang

Recent improvements in large language models (LLMs) have led many researchers to focus on building fully autonomous AI agents. This position paper questions whether this approach is the right path forward, as these autonomous systems still…

AI agents, specifically powered by large language models, have demonstrated exceptional capabilities in various applications where precision and efficacy are necessary. However, these agents come with inherent risks, including the potential…

密码学与安全 · 计算机科学 2025-03-04 Ishaan Domkundwar , Mukunda N S , Ishaan Bhola , Riddhik Kochhar

Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs), have unlocked significant potential to enhance the quality and efficiency of medical care. By introducing a novel way to interact with AI and…

Agentic systems powered by large language models (LLMs) are becoming progressively more complex and capable. Their increasing agency and expanding deployment settings attract growing attention to effective governance policies, monitoring,…

计算机与社会 · 计算机科学 2025-08-06 Garry A. Gabison , R. Patrick Xian

Recent advances in large language models (LLMs) have sparked growing interest in building fully autonomous agents. However, fully autonomous LLM-based agents still face significant challenges, including limited reliability due to…

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