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🖋 **Authors:** [Da Yin](https://wadeyin9712.github.io/), [Faeze Brahman](https://fabrahman.github.io/), [Abhilasha Ravichander](https://www.cs.cmu.edu/~aravicha/), [Khyathi Chandu](https://www.cs.cmu.edu/~kchandu/), [Kai-Wei Chang](http://web.cs.ucla.edu/~kwchang/), [Yejin Choi](https://homes.cs.washington.edu/~yejin/), [Bill Yuchen Lin](https://yuchenlin.xyz/)
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We introduce 🪄**Lumos**, Language Agents with **Unified** Data Formats, **Modular** Design, and **Open-Source** LLMs. **Lumos** unifies a suite of complex interactive tasks and achieves competitive performance with GPT-4/3.5-based and larger open-source agents.
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‼️ **Lumos** has following features:
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* 🧩 **Modular Architecture**:
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- **Lumos** consists of planning, grounding, and execution modules built based on LLAMA-2-7B.
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* 🌍 **Diverse Training Data**:
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- **Lumos** is trained with ~40K high-quality annotations from ground-truth reasoning steps in existing benchmarks with GPT-4.
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* 🚀 **Competitive Performance**:
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- 🚀 **Lumos** outperforms **GPT-4/3.5-based** agents on complex QA and web tasks, and **larger open agents** on maths tasks.
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- 🚀 **Lumos** performs better than open agent baseline formulations including **chain-of-thoughts** and **integrated** training.
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- 🚀 **Lumos** surpasses larger open LLM agents and domain-specific agents on an unseen task, WebShop.
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## 🤩 Citation
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🖋 **Authors:** [Da Yin](https://wadeyin9712.github.io/), [Faeze Brahman](https://fabrahman.github.io/), [Abhilasha Ravichander](https://www.cs.cmu.edu/~aravicha/), [Khyathi Chandu](https://www.cs.cmu.edu/~kchandu/), [Kai-Wei Chang](http://web.cs.ucla.edu/~kwchang/), [Yejin Choi](https://homes.cs.washington.edu/~yejin/), [Bill Yuchen Lin](https://yuchenlin.xyz/)
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## 🤩 Citation
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