Skip to main content
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in

Stay Ahead in the AI Revolution

Weekly digest — EPI pulse, top intelligence, fresh lineage. Free, no account.

Follow Angestrom
Global source network
Synced every 5 minutes

Continuous sync from primary AI sources — indexed, enriched, and queryable in real time.

arXivHugging FaceGitHubOpenAIAnthropicDeepMindReutersBBC TechHacker NewsReddit MLVerified feedsFunding
ANGESTROM

The Intelligence Layer of Humanity. Everything AI. All in One Place.

Angestrom connects every piece of the AI ecosystem — data, models, research, companies, tools, and people.

info@angestrom.comwww.angestrom.comLucknow, Uttar Pradesh, India

Product

  • AI Search
  • AI Models
  • Research Papers
  • Companies
  • News & Events
  • GitHub Explorer
  • APIs & Tools
  • Datasets
  • Benchmarks
  • Model lifecycle
  • Funding graph
  • Contributors
  • AI Agents

Resources

  • Weekly digest
  • Documentation
  • Tutorials
  • Guides
  • News
  • Help / Start
  • Community

Company

  • About
  • Contact
  • Privacy Policy
  • Terms of Service
  • Acceptable Use

Enterprise

  • Pricing
  • Workspace
  • Contact Sales

Developer

  • Developer Hub
  • API docs
  • GitHub

Learn

  • Learning Academy
  • Roadmaps
  • Glossary
  • AI for Beginners

Popular Topics

Loading topics…
View All Topics →
© 2026 Angestrom Intelligence Private Limited. All rights reserved.
English
Theme
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in
  1. Home
  2. /Repositories
  3. /camel-ai/camel
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 5d agoLive · 3d ago

camel-ai/camel

🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Covers

newsAlibaba's model never trained as an agent — and improved agent performance across seven benchmarksnewsAgentic AI for Robot Teams

Implements (incoming)

paperFrom Blueprint to Reality: Modeling and Applying Putnam's Social Capital Theory with LLM-based Multi-agent SimulationspaperFormal Mechanisms for Market Stability in Self-Interested Agent Societies: A Marketplace Simulation Study

Related across the graph

paperFrom Blueprint to Reality: Modeling and Applying Putnam's Social Capital Theory with LLM-based Multi-agent SimulationsnewsAgentic AI for Robot TeamspaperFormal Mechanisms for Market Stability in Self-Interested Agent Societies: A Marketplace Simulation StudynewsAlibaba's model never trained as an agent — and improved agent performance across seven benchmarks
Knowledge path·PFrom Blueprint to Reality: Modeling and Applying Putnam's Social Capital Theory with LLM-based Multi-agent Simulations→NAgentic AI for Robot Teams→PFormal Mechanisms for Market Stability in Self-Interested Agent Societies: A Marketplace Simulation Study→Rcamel-ai/camel

Topics

agentai-societiesartificial-intelligencecommunicative-aicooperative-aideep-learninglarge-language-modelsmulti-agent-systemsnatural-language-processing

Explore

Search similar →Knowledge graph →All repos →Full intelligence feed →
Graph trust82Primary
Graph score17343