Disan: Directional self-attention network for rnn/cnn-free language understanding T Shen, T Zhou, G Long, J Jiang, S Pan, C Zhang AAAI 2018, arXiv preprint arXiv:1709.04696, 2017 | 861 | 2017 |
Godec: Randomized low-rank & sparse matrix decomposition in noisy case T Zhou, D Tao International Conference on Machine Learning 3, 2, 2011 | 834 | 2011 |
Fedproto: Federated prototype learning across heterogeneous clients Y Tan, G Long, L Liu, T Zhou, Q Lu, J Jiang, C Zhang Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8432-8440, 2022 | 324 | 2022 |
Rethinking 1d-cnn for time series classification: A stronger baseline W Tang, G Long, L Liu, T Zhou, J Jiang, M Blumenstein ICLR 2022, arXiv preprint arXiv:2002.10061, 1-7, 2020 | 235* | 2020 |
Manifold elastic net: a unified framework for sparse dimension reduction T Zhou, D Tao, X Wu Data Mining and Knowledge Discovery 22 (3), 340-371, 2011 | 203 | 2011 |
Structure-augmented text representation learning for efficient knowledge graph completion B Wang, T Shen, G Long, T Zhou, Y Wang, Y Chang Proceedings of the Web Conference 2021, 1737-1748, 2021 | 196 | 2021 |
Bi-directional block self-attention for fast and memory-efficient sequence modeling T Shen, T Zhou, G Long, J Jiang, C Zhang ICLR 2018, 2018 | 176 | 2018 |
Curriculum-guided hindsight experience replay M Fang, T Zhou, Y Du, L Han, Z Zhang NeurIPS 2019, 2019 | 167 | 2019 |
Reinforced self-attention network: a hybrid of hard and soft attention for sequence modeling T Shen, T Zhou, G Long, J Jiang, S Wang, C Zhang arXiv preprint arXiv:1801.10296 (accepted by IJCAI 2018), 2018 | 154 | 2018 |
Multi-center federated learning M Xie, G Long, T Shen, T Zhou, X Wang, J Jiang, C Zhang arXiv preprint arXiv:2005.01026, 2021 | 122* | 2021 |
Federated learning from pre-trained models: A contrastive learning approach Y Tan, G Long, J Ma, L Liu, T Zhou, J Jiang Advances in Neural Information Processing Systems (NeurIPS 2022), arXiv …, 2022 | 115 | 2022 |
Robust curriculum learning: from clean label detection to noisy label self-correction T Zhou, S Wang, J Bilmes International Conference on Learning Representations, 2020 | 100 | 2020 |
Learning to propagate for graph meta-learning L Liu, T Zhou, G Long, J Jiang, C Zhang NeurIPS 2019, arXiv preprint arXiv:1909.05024, 2019 | 100 | 2019 |
HallusionBench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models T Guan, F Liu, X Wu, R Xian, Z Li, X Liu, X Wang, L Chen, F Huang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 99* | 2024 |
Alpagasus: Training a better alpaca with fewer data L Chen, S Li, J Yan, H Wang, K Gunaratna, V Yadav, Z Tang, V Srinivasan, ... arXiv preprint arXiv:2307.08701, 2023 | 98 | 2023 |
Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction Y Li, G Long, T Shen, T Zhou, L Yao, H Huo, J Jiang AAAI 2020, 2019 | 96 | 2019 |
Trustllm: Trustworthiness in large language models L Sun, Y Huang, H Wang, S Wu, Q Zhang, C Gao, Y Huang, W Lyu, ... arXiv preprint arXiv:2401.05561, 2024 | 92 | 2024 |
Diverse client selection for federated learning via submodular maximization R Balakrishnan, T Li, T Zhou, N Himayat, V Smith, J Bilmes International Conference on Learning Representations, 2022 | 88 | 2022 |
Curriculum Learning by Dynamic Instance Hardness T Zhou, S Wang, JA Bilmes NeurIPS 2020, 2020 | 84 | 2020 |
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph L Liu, T Zhou, G Long, J Jiang, L Yao, C Zhang IJCAI 2019, 2019 | 84 | 2019 |