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Introducing 🦀 CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents 🦀 CRAB provides an end-to-end and easy-to-use framework to build multimodal agents, operate environments, and create benchmarks to evaluate them, featuring three key components: - 🔀 Cross-environment support - agents can operate tasks in 📱 Android and 💻... Ubuntu. - 🕸️ Graph evaluator - provides a fine-grain evaluation metric for agents. - 🤖 Task generation - composes subtasks to automatically generate tasks. By connecting all devices to agents, 🦀CRAB unlocks greater capabilities for human-like tasks than ever before. Use 🦀 CRAB to benchmark your multimodal agents! - 👨‍💻 Check out the repository: - 📝 Read the paper: - 🌐 Find out more via the project page: - 🐫 Join our community:show more

CAMEL-AI.org

8,634 subscribers

72,807 views • 2 years ago •via X (Twitter)

Science & Technology

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8 Comments

CAMEL-AI.org2 years ago

Of course, that wouldn't be possible thanks to the amazing contributors from our @CamelAIOrg community. @TianqiXu233 (KAUST), Linyao Chen (UTokyo), Dai-jie Wu (KAUST), Yanjun Chen (CMU), @zechengzh, Xiang Yao, @Zhiqiang_Xie (Stanford), @YongchaoC (Harvard), @atasteoff (Tsinghua), Bochen Qian (SUSTech), @philiptorr (Oxford), @BernardSGhanem (KAUST), @guohao_li (Oxford)

CAMEL-AI.org2 years ago

If you are interested in learning more, check out this blog post:

omni_georgio2 years ago

🚀

Happy2 years ago

amazing

CAMEL-AI.org2 years ago

Thanks, more to come!

Tianqi Xu2 years ago

Thank @omni_georgio for making this awesome video! We target to make CRAB the best LLM agent benchmark framework.

OP2 years ago

hey @CamelAIOrg . That's promissing. Added CRAB to the new specialized directory for AI Agents and frameworks for building them. Now you can upvote it.

KALALA NZENIELE2 years ago

@DFintelligence

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