Awesome Papers: Autonomous Agents — AI Agent Framework: Live Stats & TrendScore

Live GitHub stats, community sentiment, and trend data for Awesome Papers: Autonomous Agents. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: Apr 23, 2026 • Sentiment updated: Apr 18, 2026

GitHub Statistics

Community Sentiment

Community Buzz: As seen on Dev.to, 'Andrej Karpathy's LLM Wiki pattern went viral this month. 5,000+ stars, 3,700 forks, dozens of implementations' and on GitHub, users discuss potential additions to the awesome-mcp-devtools list, showcasing a strong interest in autonomous AI agents.

Pros & Cons

What People Love

Autonomous AI agents, Gemini LLM, Dev.to community support

Common Complaints

Limited ADK support, Difficulty in building cross-cloud live agents

Biggest Positive: Autonomous AI

Biggest Negative: Limited ADK support

Why Awesome Papers: Autonomous Agents Stands Out

This collection of papers on autonomous agents is valuable because it provides a comprehensive overview of the current state of research in the field, covering both RL-based and LLM-based approaches. The papers in this collection are carefully curated and organized by topic, making it easier for researchers and developers to find relevant information. Additionally, the collection is actively maintained, with new papers added regularly, ensuring that it remains a timely and authoritative resource. The fact that it includes surveys on autonomous agents also makes it a unique and valuable resource for those looking to get an overview of the field.

Built With

Build an autonomous agent that navigates a 3D world — This repo provides a curated list of papers on RL-based and LLM-based agents to inform the development process, Build a research agent that reads and analyzes 50 papers on autonomous agents — The papers in this collection can be used to train and fine-tune the agent's understanding of the field, Build a multimodal agent that combines language and vision — The papers on LLM-based agents in this collection provide insights into how to integrate language models with other modalities, Build a continual learning system for autonomous agents — The papers on RL-based agents in this collection discuss methods for improving an agent's performance over time, Build a survey of the current state of autonomous agent research — This repo provides a comprehensive collection of papers that can be used to identify trends and gaps in the field

Getting Started

  1. Start by cloning the repository: git clone https://github.com/lafmdp/Awesome-Papers-Autonomous-Agent.git
  2. Navigate to the repository directory: cd Awesome-Papers-Autonomous-Agent
  3. Explore the papers in the collection by browsing the README or using the table of contents to find papers on specific topics
  4. Use the papers in the collection to inform the development of your own autonomous agent project, such as by using the insights from the papers on RL-based agents to design a more effective learning system
  5. Try reading some of the papers in the collection to verify that it is a valuable resource for your own research or development project

About

A collection of recent papers on building autonomous agent. Two topics included: RL-based / LLM-based agents.

Category & Tags

Category: research

Tags: agent, artificial-intelligence, autonomous-agent, awesome-paper-collection, large-language-models, machine-learning, natural-language-processing, reinforcement-learning

Market Context

Autonomous AI agents are transforming industries, with a strong focus on task automation and efficiency, as seen in the guide on snowflake.com