综述大模型与人类协作的智能系统，解析协同机制与应用前景。
LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey
- 构建人机协同框架，融合人类反馈提升大模型可靠性
- 系统梳理环境建模、交互类型、任务编排等核心组件
- 适合对人机协作、AI安全与可信计算感兴趣的 researchers
大语言模型（LLMs）的进展推动了全自主智能体的发展，但其仍面临幻觉频发、复杂任务处理能力弱及安全伦理风险高等问题，限制了在真实场景中的可信应用。为此，基于大模型的人机协作系统（LLM-HAS）引入人类提供的信息、反馈或控制，以增强系统的性能、可靠性和安全性。这类系统通过发挥人与大模型的互补优势，实现高效协同。本文首次系统性地综述了LLM-HAS，厘清基础概念，结构化呈现环境建模、人类反馈、交互类型、任务编排与通信等核心组件，探讨新兴应用场景，并分析人机协作带来的独特挑战与机遇。通过整合现有成果并提供清晰框架，旨在推动该跨学科领域的进一步研究与创新。论文列表与资源详见 https://github.com/HenryPengZou/Awesome-Human-Agent-Collaboration-Interaction-Systems。
原文摘要 · Abstract (English)
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 hallucinations, difficulty in handling complex tasks, and substantial safety and ethical risks, all of which limit their feasibility and trustworthiness in real-world applications. To overcome these limitations, LLM-based human-agent systems (LLM-HAS) incorporate human-provided information, feedback, or control into the agent system to enhance system performance, reliability, and safety. These human-agent collaboration systems enable humans and LLM-based agents to collaborate effectively by leveraging their complementary strengths. This paper provides the first comprehensive and structured survey of LLM-HAS. It clarifies fundamental concepts, systematically presents core components shaping these systems, including environment and profiling, human feedback, interaction types, orchestration, and communication, explores emerging applications, and discusses unique challenges and opportunities arising from human-AI collaboration. By consolidating current knowledge and offering a structured overview, we aim to foster further research and innovation in this rapidly evolving interdisciplinary field. Paper lists and resources are available at https://github.com/HenryPengZou/Awesome-Human-Agent-Collaboration-Interaction-Systems.
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