Toolllm: Facilitating large language models to master 16000+ real-world apis Y Qin, S Liang, Y Ye, K Zhu, L Yan, Y Lu, Y Lin, X Cong, X Tang, B Qian, ... International Conference on Learning Representations (ICLR 2024 spotlight), 2024 | 443 | 2024 |
Tool Learning with foundation Models Y Qin, S Hu, Y Lin, W Chen, N Ding, G Cui, Z Zeng, Y Huang, C Xiao, ... ACM Computing Surveys, 2023 | 244* | 2023 |
WebCPM: Interactive Web Search for Chinese Long-form Question Answering Y Qin, Z Cai, D Jin, L Yan, S Liang, K Zhu, Y Lin, X Han, N Ding, H Wang, ... Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 63 | 2023 |
Prioritizing Safeguarding Over Autonomy: Risks of LLM Agents for Science X Tang*, Q Jin*, K Zhu*, T Yuan*, Y Zhang*, W Zhou, M Qu, Y Zhao, ... ICLR 2024 LLMAgent Workshop, 2024 | 25 | 2024 |
Exploring format consistency for instruction tuning S Liang*, K Zhu*, R Tian*, Y Qin, H Wang, X Cong, Z Liu, X Liu, M Sun Transactions on Machine Learning Research, 2023 | 9 | 2023 |
Xagent: An autonomous agent for complex task solving XA Team https://github.com/OpenBMB/XAgent, 2023 | 9 | 2023 |
How Far Are We From AGI T Feng*, K Zhu*, C Jin*, J Liu*, H Tu, Z Cheng, G Lin, J You Transactions on Machine Learning Research, 2024 | 8 | 2024 |
Rageval: Scenario specific rag evaluation dataset generation framework K Zhu, Y Luo, D Xu, R Wang, S Yu, S Wang, Y Yan, Z Liu, X Han, Z Liu, ... arXiv preprint arXiv:2408.01262, 2024 | 4 | 2024 |
QASnowball: An Iterative Bootstrapping Framework for High-Quality Question-Answering Data Generation K Zhu, S Liang, X Han, Z Zheng, G Zeng, Z Liu, M Sun arXiv preprint arXiv:2309.10326, 2023 | 3 | 2023 |
Scaling Large-Language-Model-based Multi-Agent Collaboration C Qian, Z Xie, Y Wang, W Liu, K Zhu, Y Dang, Z Du, W Chen, C Yang, ... arXiv preprint arXiv:2406.07155, 2024 | 2 | 2024 |
How Far Are We From AGI: Are LLMs All We Need? T Feng, C Jin, J Liu, K Zhu, H Tu, Z Cheng, G Lin, J You Transactions on Machine Learning Research, 0 | | |