| Top-k Team Recommendation and Its Variants in Spatial Crowdsourcing D Gao, Y Tong, J She, T Song, L Chen, K Xu Data Science and Engineering 2, 136-150, 2017 | 64 | 2017 |
| Federatedscope: A flexible federated learning platform for heterogeneity Y Xie, Z Wang, D Gao, D Chen, L Yao, W Kuang, Y Li, B Ding, J Zhou arXiv preprint arXiv:2204.05011, 2022 | 59 | 2022 |
| Top-k Team Recommendation in Spatial Crowdsourcing D Gao, Y Tong, J She, T Song, L Chen, K Xu International conference on web-age information management, 191-204, 2016 | 45 | 2016 |
| pfl-bench: A comprehensive benchmark for personalized federated learning D Chen, D Gao, W Kuang, Y Li, B Ding Advances in Neural Information Processing Systems 35, 9344-9360, 2022 | 42 | 2022 |
| Text-to-sql empowered by large language models: A benchmark evaluation D Gao, H Wang, Y Li, X Sun, Y Qian, B Ding, J Zhou arXiv preprint arXiv:2308.15363, 2023 | 41 | 2023 |
| Rethinking pruning for accelerating deep inference at the edge D Gao, X He, Z Zhou, Y Tong, K Xu, L Thiele Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 24 | 2020 |
| Federatedscope-llm: A comprehensive package for fine-tuning large language models in federated learning W Kuang, B Qian, Z Li, D Chen, D Gao, X Pan, Y Xie, Y Li, B Ding, J Zhou arXiv preprint arXiv:2309.00363, 2023 | 23 | 2023 |
| Team-oriented task planning in spatial crowdsourcing D Gao, Y Tong, Y Ji, K Xu Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint …, 2017 | 17 | 2017 |
| Efficient personalized federated learning via sparse model-adaptation D Chen, L Yao, D Gao, B Ding, Y Li International Conference on Machine Learning, 5234-5256, 2023 | 14 | 2023 |
| Do emergent abilities exist in quantized large language models: An empirical study P Liu, Z Liu, ZF Gao, D Gao, WX Zhao, Y Li, B Ding, JR Wen arXiv preprint arXiv:2307.08072, 2023 | 13 | 2023 |
| Federatedscope: A comprehensive and flexible federated learning platform via message passing Y Xie, Z Wang, D Chen, D Gao, L Yao, W Kuang, Y Li, B Ding, J Zhou arXiv preprint arXiv:2204.05011 11, 2022 | 13 | 2022 |
| Data-juicer: A one-stop data processing system for large language models D Chen, Y Huang, Z Ma, H Chen, X Pan, C Ge, D Gao, Y Xie, Z Liu, J Gao, ... arXiv preprint arXiv:2309.02033, 2023 | 12 | 2023 |
| FS-REAL: Towards real-world cross-device federated learning D Chen, D Gao, Y Xie, X Pan, Z Li, Y Li, B Ding, J Zhou Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 10 | 2023 |
| Pruning meta-trained networks for on-device adaptation D Gao, X He, Z Zhou, Y Tong, L Thiele Proceedings of the 30th ACM International Conference on Information …, 2021 | 9 | 2021 |
| Pruning-aware merging for efficient multitask inference X He, D Gao, Z Zhou, Y Tong, L Thiele Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 8 | 2021 |
| Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation. CoRR abs/2308.15363 (2023) D Gao, H Wang, Y Li, X Sun, Y Qian, B Ding, J Zhou arXiv preprint arXiv:2308.15363, 2023 | 6 | 2023 |
| A benchmark for federated hetero-task learning L Yao, D Gao, Z Wang, Y Xie, W Kuang, D Chen, H Wang, C Dong, ... arXiv preprint arXiv:2206.03436, 2022 | 5 | 2022 |
| Fs-real: A real-world cross-device federated learning platform D Gao, D Chen, Z Li, Y Xie, X Pan, Y Li, B Ding, J Zhou Proceedings of the VLDB Endowment 16 (12), 4046-4049, 2023 | 3 | 2023 |
| Finding meta winning ticket to train your maml D Gao, Y Xie, Z Zhou, Z Wang, Y Li, B Ding Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 3 | 2022 |
| Federated hetero-task learning L Yao, D Gao, Z Wang, Y Xie, W Kuang, D Chen, H Wang, C Dong, ... arXiv preprint arXiv:2206.03436, 2022 | 3 | 2022 |
