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LLM-Agents-Papers

by Community

A repo lists papers related to LLM based agent

L

Agents

LLM-Agents-Papers

Added 10 July 2026

#agents #large-language-models #llm-agent #paper-list

Overview

LLM-Agents-Papers is a GitHub repository that curates a collection of academic papers focused on LLM-based agents. It serves as a centralized bibliography for researchers and developers tracking progress in autonomous agent architectures.

Best for

Best for
Researchers and developers who need a comprehensive, curated reading list on LLM-based agents

Use cases

  • Surveying recent literature on LLM agent frameworks and methodologies
  • Finding reference papers for implementing custom agent systems
  • Staying updated with the latest research trends in autonomous agents

Notes

LLM-Agents-Papers is a GitHub repository that curates a collection of academic papers focused on LLM-based agents. It serves as a centralized bibliography for researchers and developers tracking progress in autonomous agent architectures.

2,328 stars on GitHub. Last updated 2025-07-12.

Use cases

  • Surveying recent literature on LLM agent frameworks and methodologies
  • Finding reference papers for implementing custom agent systems
  • Staying updated with the latest research trends in autonomous agents

Pros

  • Well-maintained list with 2,300+ stars indicating community trust
  • Covers a broad range of topics from reasoning to tool use
  • Regularly updated with new publications

Cons

  • Contains only paper references, no code or implementation details
  • Organization relies on README structure which can become unwieldy at scale
  • No search or filtering beyond manual browsing

Indexed from awesome-llm-powered-agent and enriched against its public facts.

Pros

  • Well-maintained list with 2,300+ stars indicating community trust
  • Covers a broad range of topics from reasoning to tool use
  • Regularly updated with new publications

Cons

  • Contains only paper references, no code or implementation details
  • Organization relies on README structure which can become unwieldy at scale
  • No search or filtering beyond manual browsing