| Bias and debias in recommender system: A survey and future directions J Chen, H Dong, X Wang, F Feng, M Wang, X He ACM Transactions on Information Systems 41 (3), 1-39, 2023 | 877 | 2023 |
| AutoDebias: Learning to debias for recommendation J Chen, H Dong, Y Qiu, X He, X Xin, L Chen, G Lin, K Yang Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 173 | 2021 |
| On the equivalence of decoupled graph convolution network and label propagation H Dong, J Chen, F Feng, X He, S Bi, Z Ding, P Cui Proceedings of the Web Conference 2021, 3651-3662, 2021 | 94 | 2021 |
| Survey of code search based on deep learning Y Xie, J Lin, H Dong, L Zhang, Z Wu ACM Transactions on Software Engineering and Methodology 33 (2), 1-42, 2023 | 17 | 2023 |
| Retriever and ranker framework with probabilistic hard negative sampling for code search H Dong, J Lin, Y Leng, J Chen, Y Xie arXiv preprint arXiv:2305.04508, 2023 | 2 | 2023 |
| Data augmentation view on graph convolutional network and the proposal of Monte Carlo graph learning H Dong, Z Ding, X He, F Feng, S Bi arXiv preprint arXiv:2006.13090, 2020 | 2 | 2020 |
| Scaling Laws Behind Code Understanding Model J Lin, H Dong, Y Xie, L Zhang arXiv preprint arXiv:2402.12813, 2024 | | 2024 |
| LightAD: accelerating AutoDebias with adaptive sampling Y Qiu, H Dong, J Chen, X He JUSTC 54 (4), 0405-1-0405-10, 2024 | | 2024 |
