| Adamerging: Adaptive model merging for multi-task learning E Yang, Z Wang, L Shen, S Liu, G Guo, X Wang, D Tao International Conference on Learning Representations (ICLR 2024), 2024 | 253 | 2024 |
| Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications, and Opportunities E Yang, L Shen, G Guo, X Wang, X Cao, J Zhang, D Tao ACM Computing Surveys, 2024 | 245 | 2024 |
| A comprehensive survey of forgetting in deep learning beyond continual learning Z Wang, E Yang, L Shen, H Huang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 121 | 2024 |
| Uniform sequence better: Time interval aware data augmentation for sequential recommendation Y Dang, E Yang, G Guo, L Jiang, X Wang, X Xu, Q Sun, H Liu Proceedings of the AAAI conference on artificial intelligence 37 (4), 4225-4232, 2023 | 102 | 2023 |
| Adatask: A task-aware adaptive learning rate approach to multi-task learning E Yang, J Pan, X Wang, H Yu, L Shen, X Chen, L Xiao, J Jiang, G Guo Proceedings of the AAAI conference on artificial intelligence 37 (9), 10745 …, 2023 | 102 | 2023 |
| Representation surgery for multi-task model merging E Yang, L Shen, Z Wang, G Guo, X Chen, X Wang, D Tao International Conference on Machine Learning (ICML 2024), 2024 | 91 | 2024 |
| An efficient dataset condensation plugin and its application to continual learning E Yang, L Shen, Z Wang, T Liu, G Guo Advances in Neural Information Processing Systems 36, 67625-67642, 2023 | 48 | 2023 |
| FusionBench: A Unified Library and Comprehensive Benchmark for Deep Model Fusion A Tang, L Shen, Y Luo, E Yang, H Hu, L Zhang, B Du, D Tao Journal of Machine Learning Research, 2024 | 47* | 2024 |
| Data augmented flatness-aware gradient projection for continual learning E Yang, L Shen, Z Wang, S Liu, G Guo, X Wang Proceedings of the IEEE/CVF international conference on computer vision …, 2023 | 35 | 2023 |
| TiCoSeRec: Augmenting data to uniform sequences by time intervals for effective recommendation Y Dang, E Yang, G Guo, L Jiang, X Wang, X Xu, Q Sun, H Liu IEEE Transactions on Knowledge and Data Engineering 36 (6), 2686-2700, 2023 | 33 | 2023 |
| Discrete Trust-aware Matrix Factorization for Fast Recommendation G Guo, E Yang, L Shen, X Yang, X He International Joint Conference on Artificial Intelligence (IJCAI 2019), 1380 …, 2019 | 31 | 2019 |
| Efficient and effective weight-ensembling mixture of experts for multi-task model merging L Shen, A Tang, E Yang, G Guo, Y Luo, L Zhang, X Cao, B Du, D Tao IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 23 | 2024 |
| Graph representation learning via causal diffusion for out-of-distribution recommendation C Zhao, E Yang, Y Liang, P Lan, Y Liu, J Zhao, G Guo, X Wang Proceedings of the ACM on Web Conference 2025, 334-346, 2025 | 21* | 2025 |
| Multi-scenario and multi-task aware feature interaction for recommendation system D Song, E Yang, G Guo, L Shen, L Jiang, X Wang ACM Transactions on Knowledge Discovery from Data 18 (6), 1-20, 2024 | 19 | 2024 |
| PESI: Personalized Explanation recommendation with Sentiment Inconsistency between ratings and reviews H Wu, G Guo, E Yang, Y Luo, Y Chu, L Jiang, X Wang Knowledge-Based Systems 283, 111133, 2024 | 17 | 2024 |
| Merging on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging A Tang, E Yang, L Shen, Y Luo, H Hu, L Zhang, B Du, D Tao The Thirty-ninth Annual Conference on Neural Information Processing Systems, 2025 | 16* | 2025 |
| Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation. Y Yu*, E Yang*, G Guo, L Jiang, X Wang International Joint Conference on Artificial Intelligence (IJCAI 2023), 2415 …, 2023 | 14 | 2023 |
| Harnessing Content and Structure in ID for Multimodal Recommendation Y Liu, E Yang, Y Dang, G Guo, Q Liu, Y Liang, L Jiang, X Wang ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and …, 2025 | 12* | 2025 |
| Repeated Padding for Sequential Recommendation Y Dang, Y Liu, E Yang, G Guo, L Jiang, X Wang, J Zhao Proceedings of the 18th ACM Conference on Recommender Systems, 497-506, 2024 | 12* | 2024 |
| Distributionally robust graph out-of-distribution recommendation via diffusion model C Zhao, E Yang, Y Liang, J Zhao, G Guo, X Wang Proceedings of the ACM on Web Conference 2025, 2018-2031, 2025 | 11 | 2025 |
Guibing GuoProfessor, Software College, Northeastern University, ChinaVerified email at swc.neu.edu.cn
