| Autogen: Enabling next-gen llm applications via multi-agent conversation framework Q Wu, G Bansal, J Zhang, Y Wu, S Zhang, E Zhu, B Li, L Jiang, X Zhang, ... COLM 2024, 2023 | 393 | 2023 |
| MathChat: Converse to Tackle Challenging Math Problems with LLM Agents Y Wu, F Jia, S Zhang, H Li, E Zhu, Y Wang, YT Lee, R Peng, Q Wu, ... ICLR 2024 Workshop on Large Language Model (LLM) Agents, 2024 | 41* | 2024 |
| Targeted hyperparameter optimization with lexicographic preferences over multiple objectives S Zhang, F Jia, C Wang, Q Wu ICLR 2023 (Oral), 2022 | 22 | 2022 |
| You only compress once: Towards effective and elastic bert compression via exploit-explore stochastic nature gradient S Zhang, X Zheng, C Yang, Y Li, Y Wang, F Chao, M Wang, S Li, J Yang, ... Neurocomputing, 2021 | 21 | 2021 |
| Ddpnas: Efficient neural architecture search via dynamic distribution pruning X Zheng, C Yang, S Zhang, Y Wang, B Zhang, Y Wu, Y Wu, L Shao, R Ji IJCV 2023, 2023 | 20 | 2023 |
| IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models S Zhang, X Xia, Z Wang, LH Chen, J Liu, Q Wu, T Liu ICLR 2024, 2023 | 16 | 2023 |
| Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints X Xia, J Liu, S Zhang, Q Wu, H Wei, T Liu ICML 2024 (Spotlight), 2024 | 7* | 2024 |
| Hypertime: Hyperparameter optimization for combating temporal distribution shifts S Zhang, Y Wu, Z Zheng, Q Wu, C Wang ACM MM 2024, 2023 | 5 | 2023 |
| StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows Y Wu, T Yue, S Zhang, C Wang, Q Wu COLM 2024, 2024 | 4 | 2024 |
| Training Language Model Agents without Modifying Language Models S Zhang, J Zhang, J Liu, L Song, C Wang, R Krishna, Q Wu ICML 2024, 2024 | 4* | 2024 |
| Adaptive In-conversation Team Building for Language Model Agents L Song, J Liu, J Zhang, S Zhang, A Luo, S Wang, Q Wu, C Wang arXiv preprint arXiv:2405.19425, 2024 | 1 | 2024 |
Qingyun WuThe Pennsylvania State UniversityAdresă de e-mail confirmată pe psu.edu
