Long text generation via adversarial training with leaked information J Guo, S Lu, H Cai, W Zhang, Y Yu, J Wang The Thirty-Two AAAI Conference on Artificial Intelligence (AAAI 2018), 2017 | 604 | 2017 |
Texygen: A Benchmarking Platform for Text Generation Models Y Zhu, S Lu, L Zheng, J Guo, W Zhang, J Wang, Y Yu SIGIR 2018, 2018 | 592 | 2018 |
Neural Text Generation: Past, Present and Beyond S Lu, Y Zhu, W Zhang, J Wang, Y Yu arXiv preprint arXiv:1803.07133, 2018 | 83 | 2018 |
CoT: Cooperative Training for Generative Modeling of Discrete Data S Lu, L Yu, S Feng, Y Zhu, W Zhang International Conference on Machine Learning, 4164-4172, 2019 | 37* | 2019 |
Controllable Text Generation with Neurally-Decomposed Oracle T Meng, S Lu, N Peng, KW Chang Accepted as NeurIPS 2022 Oral Paper, 2022 | 25 | 2022 |
InsNet: An Efficient, Flexible, and Performant Insertion-based Text Generation Model S Lu, T Meng, N Peng Accepted as NeurIPS 2022 Poster Paper, 2021 | 14* | 2021 |
Neurally-Guided Structure Inference S Lu, J Mao, JB Tenenbaum, J Wu International Conference on Machine Learning, 4144--4153, 2019 | 10 | 2019 |
Open-Domain Text Evaluation via Contrastive Distribution Methods S Lu, H Liu, T Wang, A Celikyilmaz, N Peng ICML 2024 Poster Paper, 2023 | | 2023 |
DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models S Lu, W Zhao, C Tao, A Gupta, S Wu, T Chung, N Peng Forty-first International Conference on Machine Learning, 2023 | | 2023 |