| LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs Y Wang*, Z Chu*, X Ouyang, S Wang, H Hao, Y Shen, J Gu, S Xue, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (17), 19189 …, 2024 | 59* | 2024 |
| Temporal convolutional attention-based network for sequence modeling H Hao*, Y Wang*, Y Xia, J Zhao, F Shen arXiv preprint arXiv:2002.12530, 2020 | 55 | 2020 |
| Leveraging large language models for pre-trained recommender systems Z Chu, H Hao, X Ouyang, S Wang, Y Wang, Y Shen, J Gu, Q Cui, L Li, ... arXiv preprint arXiv:2308.10837, 2023 | 47 | 2023 |
| Easytpp: Towards open benchmarking the temporal point processes S Xue, X Shi, Z Chu, Y Wang, F Zhou, H Hao, C Jiang, C Pan, Y Xu, ... 2024 Twelfth International Conference on Learning Representations (ICLR 2024), 2023 | 36 | 2023 |
| Survey on Deep Learning Image Recognition in Dilemma of Small Samples Y Ge, H Liu, Y Wang, B Xu, Q Zhou, F Shen Journal of Software 33 (1), 193-210, 2021 | 32* | 2021 |
| Prompt-augmented Temporal Point Process for Streaming Event Sequence S Xue*, Y Wang*, Z Chu, X Shi, C Jiang, H Hao, G Jiang, X Feng, ... Advances in Neural Information Processing Systems (NeurIPS 2023), 2023 | 18 | 2023 |
| Llm-guided multi-view hypergraph learning for human-centric explainable recommendation Z Chu*, Y Wang*, Q Cui, L Li, W Chen, S Li, Z Qin, K Ren arXiv preprint arXiv:2401.08217, 2024 | 14 | 2024 |
| A Causal Explainable Guardrails for Large Language Models Z Chu*, Y Wang*, L Li, Z Wang, Z Qin, K Ren Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications …, 2024 | 11 | 2024 |
| Professional Agents--Evolving Large Language Models into Autonomous Experts with Human-Level Competencies Z Chu, Y Wang, F Zhu, L Yu, L Li, J Gu arXiv preprint arXiv:2402.03628, 2024 | 9 | 2024 |
| Continual Learning in Predictive Autoscaling H Hao, Z Chu, S Zhu, G Jiang, Y Wang, C Jiang, J Zhang, W Jiang, S Xue, ... Conference on Information and Knowledge Management (CIKM 2023), 2023 | 5 | 2023 |
| Enhancing Event Sequence Modeling with Contrastive Relational Inference Y Wang, Z Chu, T Zhou, C Jiang, H Hao, M Zhu, X Cai, Q Cui, L Li, ... ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2023 | 3 | 2023 |
| Dynamic auxiliary soft labels for decoupled learning Y Wang, Y Zhang, F Shen, J Zhao Neural Networks 151, 132-142, 2022 | 3 | 2022 |
| Flow-Based End-to-End Model for Hierarchical Time Series Forecasting via Trainable Attentive-Reconciliation S Wang, Y Sun, Y Wang, F Zhou, LT Ma, J Zhang, YF Zheng International Conference on Database Systems for Advanced Applications …, 2023 | 2 | 2023 |
| Explainable behavior cloning: Teaching large language model agents through learning by demonstration Y Guan, D Wang, Y Wang, H Wang, R Sun, C Zhuang, J Gu, Z Chu arXiv preprint arXiv:2410.22916, 2024 | 1 | 2024 |
| Review Neural Networks about Image Transformation Based on IGC Learning Framework with Annotated Information Y Yan, S Yang, Y Wang, J Zhao, F Shen arXiv preprint arXiv:2206.10155, 2022 | 1 | 2022 |
| Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference Y Wang, Z Chu, T Zhou, C Jiang, H Hao, M Zhu, X Cai, Q Cui, L Li, ... IEEE International Conference on Data Mining (ICDM 2023) Workshop-AI4TS …, 2023 | | 2023 |
| Improving the Transferability of Time Series Forecasting with Decomposition Adaptation Y Gao*, Y Wang*, Q Wang arXiv preprint arXiv:2307.00066, 2023 | | 2023 |