| 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, ... ICLR 2024 Workshop on LLMAgents, 2023 | 179 | 2023 |
| An empirical study on challenging math problem solving with gpt-4 Y Wu, F Jia, S Zhang, Q Wu, H Li, E Zhu, Y Wang, YT Lee, R Peng, ... ICLR 2024 Workshop on LLMAgents, 2023 | 28 | 2023 |
| 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, ... arXiv preprint arXiv:2106.02435, 2021 | 21 | 2021 |
| Targeted hyperparameter optimization with lexicographic preferences over multiple objectives S Zhang, F Jia, C Wang, Q Wu ICLR 2023, 2022 | 19 | 2022 |
| 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 131 (5), 1234-1249, 2023 | 18 | 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 | 6 | 2023 |
| Hypertime: Hyperparameter optimization for combating temporal distribution shifts S Zhang, Y Wu, Z Zheng, Q Wu, C Wang arXiv preprint arXiv:2305.18421, 2023 | 5 | 2023 |
| Coreset selection with prioritized multiple objectives X Xia, J Liu, S Zhang, Q Wu, T Liu arXiv preprint arXiv:2311.08675, 2023 | 4 | 2023 |
| StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows Y Wu, T Yue, S Zhang, C Wang, Q Wu arXiv preprint arXiv:2403.11322, 2024 | | 2024 |
| Training Language Model Agents without Modifying Language Models S Zhang, J Zhang, J Liu, L Song, C Wang, R Krishna, Q Wu arXiv preprint arXiv:2402.11359, 2024 | | 2024 |
Qingyun WuPenn State UniversityE-mail confirmado em psu.edu
