Unverified50% confidenceFactExact time
The agent paradigm refers to upgrading LLMs from question-answering systems to executors capable of autonomous planning, tool invocation, and continuous interaction with the environment.
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9/18/2026
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Unverified科研自动化 Agent 通常基于 LLM 的工具调用与任务规划能力，结合代码执行沙箱、文件系统访问、学术检索及 GitHub/Hugging Face API 等外部工具，形成感知-规划-执行-反馈的闭环79% similarUnverifiedTraditional LLMs operate in a passive 'one question, one answer' mode, whereas AI Agents possess proactive closed-loop execution capabilities.78% similarUnverifiedIn the Agent architecture, the LLM is responsible for intent understanding and step planning, while actual execution is delegated to external tools such as calculators, search engines, and API endpoints.78% similarUnverifiedThe rise of the Agent architectural paradigm is closely related to the maturation of LLM tool-calling capabilities77% similarUnverifiedAgents possess three core capabilities—autonomous planning, autonomous execution, and environmental interaction—which are the fundamental characteristics that distinguish Agents from ordinary LLM applications.77% similar
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