Contributor Guide
Research
For technical details, please check our technical report and research publications.
- AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework. Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Shaokun Zhang, Erkang Zhu, Beibin Li, Li Jiang, Xiaoyun Zhang and Chi Wang. ArXiv 2023.
- Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference. Chi Wang, Susan Xueqing Liu, Ahmed H. Awadallah. AutoML’23.
- An Empirical Study on Challenging Math Problem Solving with GPT-4. Yiran Wu, Feiran Jia, Shaokun Zhang, Hangyu Li, Erkang Zhu, Yue Wang, Yin Tat Lee, Richard Peng, Qingyun Wu, Chi Wang. ArXiv preprint arXiv:2306.01337 (2023).
- EcoAssistant: Using LLM Assistant More Affordably and Accurately. Jieyu Zhang, Ranjay Krishna, Ahmed H. Awadallah, Chi Wang. ArXiv preprint arXiv:2310.03046 (2023).
- Towards better Human-Agent Alignment: Assessing Task Utility in LLM-Powered Applications. Negar Arabzadeh, Julia Kiseleva, Qingyun Wu, Chi Wang, Ahmed Awadallah, Victor Dibia, Adam Fourney, Charles Clarke. ArXiv preprint arXiv:2402.09015 (2024).
- Training Language Model Agents without Modifying Language Models. Shaokun Zhang, Jieyu Zhang, Jiale Liu, Linxin Song, Chi Wang, Ranjay Krishna, Qingyun Wu. ICML’24.
- AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks. Yifan Zeng, Yiran Wu, Xiao Zhang, Huazheng Wang, Qingyun Wu. ArXiv preprint arXiv:2403.04783 (2024).
- StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows. Yiran Wu, Tianwei Yue, Shaokun Zhang, Chi Wang, Qingyun Wu. ArXiv preprint arXiv:2403.11322 (2024).