| Interpretable deep learning: Interpretation, interpretability, trustworthiness, and beyond X Li, H Xiong, X Li, X Wu, X Zhang, J Liu, J Bian, D Dou Knowledge and Information Systems 64 (12), 3197-3234, 2022 | 394 | 2022 |
| Explicit inductive bias for transfer learning with convolutional networks LI Xuhong, Y Grandvalet, F Davoine International Conference on Machine Learning, 2825-2834, 2018 | 394 | 2018 |
| From distributed machine learning to federated learning: A survey J Liu, J Huang, Y Zhou, X Li, S Ji, H Xiong, D Dou Knowledge and Information Systems 64 (4), 885-917, 2022 | 294 | 2022 |
| Transfer learning in computer vision tasks: Remember where you come from X Li, Y Grandvalet, F Davoine, J Cheng, Y Cui, H Zhang, S Belongie, ... Image and Vision Computing 93, 103853, 2020 | 111 | 2020 |
| A baseline regularization scheme for transfer learning with convolutional neural networks X Li, Y Grandvalet, F Davoine Pattern Recognition 98, 107049, 2020 | 64 | 2020 |
| G-LIME: Statistical learning for local interpretations of deep neural networks using global priors X Li, H Xiong, X Li, X Zhang, J Liu, H Jiang, Z Chen, D Dou Artificial Intelligence 314, 103823, 2023 | 39 | 2023 |
| Cross-task transfer for geotagged audiovisual aerial scene recognition D Hu, X Li, L Mou, P Jin, D Chen, L Jing, X Zhu, D Dou Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 38* | 2020 |
| Explaining information flow inside vision transformers using markov chain T Yuan, X Li, H Xiong, H Cao, D Dou eXplainable AI approaches for debugging and diagnosis., 2021 | 30 | 2021 |
| Muscle: Multi-task self-supervised continual learning to pre-train deep models for x-ray images of multiple body parts W Liao, H Xiong, Q Wang, Y Mo, X Li, Y Liu, Z Chen, S Huang, D Dou International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 29 | 2022 |
| Multi-purpose RNA language modelling with motif-aware pretraining and type-guided fine-tuning N Wang, J Bian, Y Li, X Li, S Mumtaz, L Kong, H Xiong Nature Machine Intelligence, 1-10, 2024 | 23 | 2024 |
| When search engine services meet large language models: visions and challenges H Xiong, J Bian, Y Li, X Li, M Du, S Wang, D Yin, S Helal IEEE Transactions on Services Computing, 2024 | 20 | 2024 |
| InterpretDL: Explaining Deep Models in PaddlePaddle X Li, H Xiong, X Li, X Wu, Z Chen, D Dou Journal of Machine Learning Research 23 (197), 1-6, 2022 | 16 | 2022 |
| HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization Q Peng, Y Chai, X Li arXiv preprint arXiv:2402.16694, 2024 | 15 | 2024 |
| Beyond Intuition: Rethinking Token Attributions inside Transformers J Chen, X Li, L Yu, D Dou, H Xiong Transactions on Machine Learning Research, 2023 | 14 | 2023 |
| : A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models X Li, M Du, J Chen, Y Chai, H Lakkaraju, H Xiong Advances in Neural Information Processing Systems 36, 1630-1643, 2023 | 13* | 2023 |
| Feynman: Federated Learning-Based Advertising for Ecosystems-Oriented Mobile Apps Recommendation J Bian, J Huang, S Ji, Y Liao, X Li, Q Wang, J Zhou, D Dou, Y Wang, ... IEEE Transactions on Services Computing 16 (5), 3361-3372, 2023 | 11 | 2023 |
| Cross-model consensus of explanations and beyond for image classification models: An empirical study X Li, H Xiong, S Huang, S Ji, D Dou Machine Learning 112 (5), 1627-1662, 2023 | 11 | 2023 |
| Interpretable machine learning for weather and climate prediction: A review R Yang, J Hu, Z Li, J Mu, T Yu, J Xia, X Li, A Dasgupta, H Xiong Atmospheric Environment, 120797, 2024 | 9 | 2024 |
| Representation transfer by optimal transport X Li, Y Grandvalet, R Flamary, N Courty, D Dou arXiv preprint arXiv:2007.06737, 2020 | 9 | 2020 |
| Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective H Xiong, X Zhang, J Chen, X Sun, Y Li, Z Sun, M Du arXiv preprint arXiv:2401.04374, 2024 | 6 | 2024 |
Haoyi XiongMicrosoftE-mailová adresa ověřena na: microsoft.com