LLM Agent Papers is an open-source repository that curates research papers related to large language model agents and autonomous AI systems. The project organizes academic literature that explores how language models can act as agents capable of reasoning, planning, and interacting with external tools or environments. Rather than providing software code, the repository functions as a structured knowledge base that helps researchers navigate the rapidly expanding field of agent-based AI research. Papers are categorized into thematic groups covering topics such as tool use, planning algorithms, reasoning strategies, and multi-agent collaboration. The repository helps readers understand how agent architectures are evolving and how they are applied in domains such as robotics, software automation, and decision-making systems. It also provides references to influential works that define the conceptual foundations of agent-based AI systems.

Features

  • Curated collection of research papers related to LLM-based agents
  • Categorization of papers by agent architectures and research topics
  • Coverage of planning, reasoning, and tool-use strategies in AI agents
  • Resource for understanding emerging agent-based AI systems
  • Regular updates that track new research developments in the field
  • Educational reference for researchers studying autonomous AI agents

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Registered

2026-03-05