| TUTA: Tree-based Transformers for Generally Structured Table Pre-training Z Wang, H Dong, R Jia, J Li, Z Fu, S Han, D Zhang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 60* | 2021 |
| Tablesense: Spreadsheet table detection with convolutional neural networks H Dong, S Liu, S Han, Z Fu, D Zhang Proceedings of the AAAI conference on artificial intelligence 33 (01), 69-76, 2019 | 44 | 2019 |
| Visualization assessment: A machine learning approach X Fu, Y Wang, H Dong, W Cui, H Zhang 2019 IEEE Visualization Conference (VIS), 126-130, 2019 | 19 | 2019 |
| Semantic structure extraction for spreadsheet tables with a multi-task learning architecture H Dong, S Liu, Z Fu, S Han, D Zhang Workshop on Document Intelligence at NeurIPS 2019, 2019 | 18 | 2019 |
| Hitab: A hierarchical table dataset for question answering and natural language generation Z Cheng, H Dong, Z Wang, R Jia, J Guo, Y Gao, S Han, JG Lou, D Zhang arXiv preprint arXiv:2108.06712 （ACL 2022 main track）, 2021 | 17 | 2021 |
| Table Pretraining: A Survey on Model Architectures, Pretraining Objectives, and Downstream Tasks H Dong, Z Cheng, X He, M Zhou, A Zhou, F Zhou, A Liu, S Han, D Zhang arXiv preprint arXiv:2201.09745 Will appear in IJCAI'2022 survey track, 2022 | 14 | 2022 |
| FORTAP: Using Formulae for Numerical-Reasoning-Aware Table Pretraining Z Cheng, H Dong, F Cheng, R Jia, P Wu, S Han, D Zhang arXiv preprint arXiv:2109.07323 (ACL 2022 main track), 2021 | 10 | 2021 |
| Unsupervised dictionary learning with Fisher discriminant for clustering M Xu, H Dong, C Chen, L Li Neurocomputing 194, 65-73, 2016 | 9 | 2016 |
| PLOG: Table-to-Logic Pretraining for Logical Table-to-Text Generation A Liu, H Dong, N Okazaki, S Han, D Zhang arXiv preprint arXiv:2205.12697, 2022 | 5 | 2022 |
| Tacube: Pre-computing data cubes for answering numerical-reasoning questions over tabular data F Zhou, M Hu, H Dong, Z Cheng, S Han, D Zhang arXiv preprint arXiv:2205.12682, 2022 | 5 | 2022 |
| Auto-formatting of a data table H Dong, FU Zhouyu, S Han, D Zhang US Patent App. 17/291,818, 2022 | 5 | 2022 |
| Semantic table structure identification in spreadsheets Y Zhang, X Lv, H Dong, W Dou, S Han, D Zhang, J Wei, D Ye Proceedings of the 30th ACM SIGSOFT International Symposium on Software …, 2021 | 5 | 2021 |
| Neural Formatting for Spreadsheet Tables H Dong, J Wang, Z Fu, S Han, D Zhang CIKM'2020 (among five best paper nominees in full research track), 305-314, 2020 | 4 | 2020 |
| Table detection in spreadsheet D Haoyu, H Shi, F Zhouyu, Z Dongmei US Patent App. 17/057,097, 2021 | 3* | 2021 |
| Reflection of Thought: Inversely Eliciting Numerical Reasoning in Language Models via Solving Linear Systems F Zhou, H Dong, Q Liu, Z Cheng, S Han, D Zhang arXiv preprint arXiv:2210.05075, 2022 | 2 | 2022 |
| Learning formatting style transfer and structure extraction for spreadsheet tables with a hybrid neural network architecture H Dong, J Yang, S Han, D Zhang Proceedings of the 29th ACM International Conference on Information …, 2020 | 2 | 2020 |
| Learning Dynamic GMM for Attention Distribution on Single-face Videos Y Ren, Z Wang, M Xu, H Dong, S Li Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 1 | 2017 |
| Spreadsheet table transformation H Dong, S Han, D Zhang, JM Halberstam, LYU Xiao US Patent App. 17/627,049, 2022 | | 2022 |
| Inversely Eliciting Numerical Reasoning in Language Models via Solving Linear Systems F Zhou, H Dong, Q Liu, Z Cheng, S Han, D Zhang | | |
Dongmei ZhangMicrosoft ResearchVerified email at microsoft.com
