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This preprint introduces "Agentic Large Language Models," exploring the paradigm shift where LLMs transition from passive text generators to autonomous agents capable of interacting with real-world environments and other models. The work addresses fundamental questions regarding how these systems execute actions, coordinate with peers, and impact user decision-making processes.
Surse care acoperăarXiv, AI Alignment Forum, Analytics Vidhya, Quantum Frontiers
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Agentic Large Language Models

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2610.13455v1 Announce Type: new Abstract: Large language models (LLMs) have taken the world by storm. Their ability to communicate with us in our own language, and to reason about our world, has made them a favorite tool for writing, answering questions, and much more. Their answers already influence our decisions and our actions. What would happen if LLMs themselves could act in the world directly? What would happen if LLMs could interact with each other? Agentic LLMs combine the power of large language models with the ability to act in the real world. In this book we will discuss how agentic LLMs work, how they act, how they interact, and what this means for us, as users.

Abstract:Large language models (LLMs) have taken the world by storm. Their ability to communicate with us in our own language, and to reason about our world, has made them a favorite tool for writing, answering questions, and much more. Their answers already influence our decisions and our actions. What would happen if LLMs themselves could act in the world directly? What would happen if LLMs could interact with each other? Agentic LLMs combine the power of large language models with the ability to act in the real world. In this book we will discuss how agentic LLMs work, how they act, how they interact, and what this means for us, as users.

Artificial Intelligence (cs.AI)

arXiv:2610.13455 [cs.AI]

(or arXiv:2610.13455v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2610.13455 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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