| Qwen technical report J Bai, S Bai, Y Chu, Z Cui, K Dang, X Deng, Y Fan, W Ge, Y Han, F Huang, ... arXiv preprint arXiv:2309.16609, 2023 | 1060 | 2023 |
| Ofa: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework P Wang, A Yang, R Men, J Lin, S Bai, Z Li, J Ma, C Zhou, J Zhou, H Yang International conference on machine learning, 23318-23340, 2022 | 1008 | 2022 |
| Disentangled graph convolutional networks J Ma, P Cui, K Kuang, X Wang, W Zhu International Conference on Machine Learning (ICML 2019), 4212-4221, 2019 | 372 | 2019 |
| Learning disentangled representations for recommendation J Ma, C Zhou, P Cui, H Yang, W Zhu Advances in Neural Information Processing Systems (NeurIPS 2019) 32, 2019 | 346 | 2019 |
| Disentangled self-supervision in sequential recommenders J Ma, C Zhou, H Yang, P Cui, X Wang, W Zhu Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 214 | 2020 |
| Qwen2 technical report A Yang, B Yang, B Hui, B Zheng, B Yu, C Zhou, C Li, C Li, D Liu, F Huang, ... arXiv preprint arXiv:2407.10671, 2024 | 195 | 2024 |
| M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems Z Cui, J Ma, C Zhou, J Zhou, H Yang arXiv preprint arXiv:2205.08084, 2022 | 169 | 2022 |
| Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems C Zhou, J Ma, J Zhang, J Zhou, H Yang Proceedings of the 27th ACM SIGKDD International Conference on Knowledge …, 2021 | 150 | 2021 |
| M6: A chinese multimodal pretrainer J Lin, R Men, A Yang, C Zhou, M Ding, Y Zhang, P Wang, A Wang, ... arXiv preprint arXiv:2103.00823, 2021 | 135 | 2021 |
| Edge-cloud polarization and collaboration: A comprehensive survey for ai J Yao, S Zhang, Y Yao, F Wang, J Ma, J Zhang, Y Chu, L Ji, K Jia, T Shen, ... IEEE Transactions on Knowledge and Data Engineering 35 (7), 6866-6886, 2022 | 90 | 2022 |
| M6-UFC: Unifying Multi-Modal Controls for Conditional Image Synthesis via Non-Autoregressive Generative Transformers Z Zhang, J Ma, C Zhou, R Men, Z Li, M Ding, J Tang, J Zhou, H Yang Advances in Neural Information Processing Systems (NeurIPS 2021), 2021 | 78* | 2021 |
| Depthlgp: Learning embeddings of out-of-sample nodes in dynamic networks J Ma, P Cui, W Zhu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 77 | 2018 |
| Intention-aware sequential recommendation with structured intent transition H Li, X Wang, Z Zhang, J Ma, P Cui, W Zhu IEEE Transactions on Knowledge and Data Engineering 34 (11), 5403-5414, 2021 | 64 | 2021 |
| Disentangled representation learning for recommendation X Wang, H Chen, Y Zhou, J Ma, W Zhu IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (1), 408-424, 2022 | 56 | 2022 |
| Counterfactual prediction for bundle treatment H Zou, P Cui, B Li, Z Shen, J Ma, H Yang, Y He Advances in Neural Information Processing Systems 33, 19705-19715, 2020 | 56 | 2020 |
| Autone: Hyperparameter optimization for massive network embedding K Tu, J Ma, P Cui, J Pei, W Zhu Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 54 | 2019 |
| Hierarchical taxonomy aware network embedding J Ma, P Cui, X Wang, W Zhu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 51 | 2018 |
| Global-to-local modeling for video-based 3d human pose and shape estimation X Shen, Z Yang, X Wang, J Ma, C Zhou, Y Yang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 27 | 2023 |
| Pretrained diffusion models for unified human motion synthesis J Ma, S Bai, C Zhou arXiv preprint arXiv:2212.02837, 2022 | 22 | 2022 |
| Variational Autoencoders for Highly Multivariate Spatial Point Processes Intensities B Yuan, X Wang, J Ma, C Zhou, AL Bertozzi, H Yang Eighth International Conference on Learning Representations (ICLR 2020), 2020 | 15 | 2020 |
Chang ZhouAlibaba Group; Peking University (zhouchang@pku.edu.cn)Zweryfikowany adres z pku.edu.cn
