| Modeling long-and short-term temporal patterns with deep neural networks G Lai, WC Chang, Y Yang, H Liu The 41st international ACM SIGIR conference on research & development in …, 2018 | 2046 | 2018 |
| Race: Large-scale reading comprehension dataset from examinations G Lai, Q Xie, H Liu, Y Yang, E Hovy arXiv preprint arXiv:1704.04683, 2017 | 1349 | 2017 |
| Explicit factor models for explainable recommendation based on phrase-level sentiment analysis Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu, S Ma Proceedings of the 37th international ACM SIGIR conference on Research …, 2014 | 970 | 2014 |
| Funnel-transformer: Filtering out sequential redundancy for efficient language processing Z Dai, G Lai, Y Yang, Q Le Advances in neural information processing systems 33, 4271-4282, 2020 | 222 | 2020 |
| Large-scale cloze test dataset created by teachers Q Xie, G Lai, Z Dai, E Hovy arXiv preprint arXiv:1711.03225, 2017 | 103* | 2017 |
| Daily-aware personalized recommendation based on feature-level time series analysis Y Zhang, M Zhang, Y Zhang, G Lai, Y Liu, H Zhang, S Ma Proceedings of the 24th international conference on world wide web, 1373-1383, 2015 | 92 | 2015 |
| Stochastic wavenet: A generative latent variable model for sequential data G Lai, B Li, G Zheng, Y Yang arXiv preprint arXiv:1806.06116, 2018 | 29 | 2018 |
| Bridging the domain gap in cross-lingual document classification G Lai, B Oguz, Y Yang, V Stoyanov arXiv preprint arXiv:1909.07009, 2019 | 17 | 2019 |
| Unsupervised parallel corpus mining on web data G Lai, Z Dai, Y Yang arXiv preprint arXiv:2009.08595, 2020 | 8 | 2020 |
| Re-examination of the role of latent variables in sequence modeling G Lai, Z Dai, Y Yang, S Yoo Advances in Neural Information Processing Systems 32, 2019 | 8 | 2019 |
| Learning graph convolution filters from data manifold G Lai, H Liu, Y Yang | 8 | 2018 |
| Inflection-2 InflectionAI https://inflection.ai/inflection-2, 2023 | 5* | 2023 |
| Correlation-aware change-point detection via graph neural networks R Zhang, Y Hao, D Yu, WC Chang, G Lai, Y Yang Neural Information Processing: 27th International Conference, ICONIP 2020 …, 2020 | 5 | 2020 |
| Correlation-aware unsupervised change-point detection via graph neural networks R Zhang, Y Hao, D Yu, WC Chang, G Lai, Y Yang arXiv preprint arXiv:2004.11934, 2020 | 3 | 2020 |
| Explainable Unsupervised Change-point Detection via Graph Neural Networks R Zhang, Y Hao, D Yu, WC Chang, G Lai, Y Yang arXiv preprint arXiv:2004.11934, 2020 | 2 | 2020 |
| Exploring machine learning models for cloud microphysics parameterizations Y Liu, J Chen, G Lai, Y Yang, S Yoo AGU Fall Meeting Abstracts 2018, A21K-2858, 2018 | 1 | 2018 |
| Learning depthwise separable graph convolution from data manifold G Lai, H Liu, Y Yang arXiv preprint arXiv:1710.11577, 2017 | 1 | 2017 |
| Neural Sequential Modeling and Applications G Lai Google Research, 2021 | | 2021 |
