| Big bird: Transformers for longer sequences M Zaheer, G Guruganesh, KA Dubey, J Ainslie, C Alberti, S Ontanon, ... Advances in neural information processing systems 33, 17283-17297, 2020 | 973 | 2020 |
| ETC: Encoding long and structured inputs in transformers J Ainslie, S Ontanon, C Alberti, V Cvicek, Z Fisher, P Pham, A Ravula, ... arXiv preprint arXiv:2004.08483, 2020 | 195 | 2020 |
| Strongly interacting quantum gases in one-dimensional traps L Yang, L Guan, H Pu Physical Review A 91 (4), 043634, 2015 | 72 | 2015 |
| Learning to extract attribute value from product via question answering: A multi-task approach Q Wang, L Yang, B Kanagal, S Sanghai, D Sivakumar, B Shu, Z Yu, ... Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 39 | 2020 |
| Deep learning-enhanced variational Monte Carlo method for quantum many-body physics L Yang, Z Leng, G Yu, A Patel, WJ Hu, H Pu Physical Review Research 2 (1), 012039, 2020 | 37 | 2020 |
| Bose-Fermi mapping and a multibranch spin-chain model for strongly interacting quantum gases in one dimension: Dynamics and collective excitations L Yang, H Pu Physical Review A 94 (3), 033614, 2016 | 28 | 2016 |
| Mave: A product dataset for multi-source attribute value extraction L Yang, Q Wang, Z Yu, A Kulkarni, S Sanghai, B Shu, J Elsas, B Kanagal Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 13 | 2022 |
| One-body density matrix and momentum distribution of strongly interacting one-dimensional spinor quantum gases L Yang, H Pu Physical Review A 95 (5), 051602, 2017 | 11 | 2017 |
| Scalable variational Monte Carlo with graph neural ansatz L Yang, W Hu, L Li arXiv preprint arXiv:2011.12453, 2020 | 10 | 2020 |
| Dynamical Fermionization in One-Dimensional Spinor Quantum Gases SS Alam, T Skaras, L Yang, H Pu Physical Review Letters 127 (2), 023002, 2021 | 8 | 2021 |
| Big bird: Transformers for longer sequences. arXiv 2020 M Zaheer, G Guruganesh, A Dubey, J Ainslie, C Alberti, S Ontanon, ... arXiv preprint arXiv:2007.14062, 2007 | 8 | 2007 |
| Predicting relapse in patients with triple negative breast cancer (tnbc) using a deep-learning approach G Yu, X Li, TF He, T Gruosso, D Zuo, M Souleimanova, VM Ramos, ... Frontiers in Physiology 11, 511071, 2020 | 3 | 2020 |
| Learning to Generate Question by Asking Question: A Primal-Dual Approach with Uncommon Word Generation Q Wang, L Yang, X Quan, F Feng, D Liu, Z Xu, S Wang, H Ma Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 1 | 2022 |
| Generalized Bose–Fermi mapping and strong coupling ansatz wavefunction for one dimensional strongly interacting spinor quantum gases L Yang, SS Alam, H Pu Journal of Physics A: Mathematical and Theoretical 55 (46), 464005, 2022 | 1 | 2022 |
| SMARTAVE: Structured Multimodal Transformer for Product Attribute Value Extraction Q Wang, L Yang, J Wang, J Krishnan, B Dai, S Wang, Z Xu, M Khabsa, ... Findings of the Association for Computational Linguistics: EMNLP 2022, 263-276, 2022 | | 2022 |
| Dynamical Fermionization and Scaling Behaviour for a Strongly Repulsive Spinor Gas after Quench SS Alam, T Skaras, L Yang, H Pu Bulletin of the American Physical Society 65, 2020 | | 2020 |
| Deep Convolutional Neural Networks for Quantum 1D Spin Chains SS Alam, L Yang, W Hu, Y Ju, H Pu, A Patel APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts 2020 …, 2020 | | 2020 |
| Exploring Deep Convolutional Network Architectures for Quantum 1D Spin Chains SS Alam, L Yang, Y Ju, W Hu, H Pu, A Patel APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts 2020 …, 2020 | | 2020 |
| Dynamical Fermionization, Tan Contact, and Scalings for a Strongly Interacting Gas after quench SS Alam, T Skaras, L Yang, H Pu APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts 2019 …, 2019 | | 2019 |
| Strongly Interacting One-Dimensional Spinor Quantum Gases L Yang Rice University, 2019 | | 2019 |
Qifan WangSenior Staff Research Scientist, Meta AIVerified email at fb.com
