Deep graph library: Towards efficient and scalable deep learning on graphs MY Wang ICLR workshop on representation learning on graphs and manifolds, 2019 | 632 | 2019 |
Bert-attack: Adversarial attack against bert using bert L Li, R Ma, Q Guo, X Xue, X Qiu arXiv preprint arXiv:2004.09984, 2020 | 442 | 2020 |
Star-transformer Q Guo, X Qiu, P Liu, Y Shao, X Xue, Z Zhang arXiv preprint arXiv:1902.09113, 2019 | 260 | 2019 |
A unified generative framework for various NER subtasks H Yan, T Gui, J Dai, Q Guo, Z Zhang, X Qiu arXiv preprint arXiv:2106.01223, 2021 | 188 | 2021 |
Colake: Contextualized language and knowledge embedding T Sun, Y Shao, X Qiu, Q Guo, Y Hu, X Huang, Z Zhang arXiv preprint arXiv:2010.00309, 2020 | 138 | 2020 |
Multi-scale self-attention for text classification Q Guo, X Qiu, P Liu, X Xue, Z Zhang Proceedings of the AAAI conference on artificial intelligence 34 (05), 7847-7854, 2020 | 71 | 2020 |
Bp-transformer: Modelling long-range context via binary partitioning Z Ye, Q Guo, Q Gan, X Qiu, Z Zhang arXiv preprint arXiv:1911.04070, 2019 | 68 | 2019 |
First step toward model-free, anonymous object tracking with recurrent neural networks Q Gan, Q Guo, Z Zhang, K Cho arXiv preprint arXiv:1511.06425, 2015 | 67 | 2015 |
Cyclegt: Unsupervised graph-to-text and text-to-graph generation via cycle training Q Guo, Z Jin, X Qiu, W Zhang, D Wipf, Z Zhang arXiv preprint arXiv:2006.04702, 2020 | 45 | 2020 |
Genwiki: A dataset of 1.3 million content-sharing text and graphs for unsupervised graph-to-text generation Z Jin, Q Guo, X Qiu, Z Zhang Proceedings of the 28th International Conference on Computational …, 2020 | 36 | 2020 |
Deep graph library: towards efficient and scalable deep learning on graphs. CoRR abs/1909.01315 (2019) M Wang, L Yu, QG Da Zheng, Y Gai, Z Ye, M Li, J Zhou, Q Huang, C Ma, ... arXiv preprint arXiv:1909.01315, 2019 | 27 | 2019 |
Syntax-guided text generation via graph neural network Q Guo, X Qiu, X Xue, Z Zhang Science China Information Sciences 64, 1-10, 2021 | 25 | 2021 |
Joint parsing and generation for abstractive summarization K Song, L Lebanoff, Q Guo, X Qiu, X Xue, C Li, D Yu, F Liu Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8894-8901, 2020 | 22 | 2020 |
Do Large Language Models Know What They Don't Know? Z Yin, Q Sun, Q Guo, J Wu, X Qiu, X Huang arXiv preprint arXiv:2305.18153, 2023 | 21 | 2023 |
𝒫2: A Plan-and-Pretrain Approach for Knowledge Graph-to-Text Generation: A Plan-and-Pretrain Approach for Knowledge Graph-to-Text Generation Q Guo, Z Jin, N Dai, X Qiu, X Xue, D Wipf, Z Zhang Proceedings of the 3rd International Workshop on Natural Language Generation …, 2020 | 20 | 2020 |
Low-rank and locality constrained self-attention for sequence modeling Q Guo, X Qiu, X Xue, Z Zhang IEEE/ACM Transactions on Audio, Speech, and Language Processing 27 (12 …, 2019 | 20 | 2019 |
Fork or fail: Cycle-consistent training with many-to-one mappings Q Guo, Z Jin, Z Wang, X Qiu, W Zhang, J Zhu, Z Zhang, W David International Conference on Artificial Intelligence and Statistics, 1828-1836, 2021 | 12 | 2021 |
Deep graph library, 2018 M Wang, L Yu, Q Gan, D Zheng, Y Gai, Z Ye, M Li, J Zhou, Q Huang, ... URL http://dgl. ai, 0 | 7 | |
Full Parameter Fine-tuning for Large Language Models with Limited Resources K Lv, Y Yang, T Liu, Q Gao, Q Guo, X Qiu arXiv preprint arXiv:2306.09782, 2023 | 5 | 2023 |
Dialogue meaning representation for task-oriented dialogue systems X Hu, J Dai, H Yan, Y Zhang, Q Guo, X Qiu, Z Zhang arXiv preprint arXiv:2204.10989, 2022 | 4 | 2022 |