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| 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 | 424 | 2020 |
| 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 | 100 | 2020 |
| Strongly interacting quantum gases in one-dimensional traps L Yang, L Guan, H Pu Physical Review A 91 (4), 043634, 2015 | 82 | 2015 |
| 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 | 67 | 2022 |
| 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 | 44 | 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 | 32 | 2016 |
| MixPAVE: Mix-prompt tuning for few-shot product attribute value extraction L Yang, Q Wang, J Wang, X Quan, F Feng, Y Chen, M Khabsa, S Wang, ... Findings of the association for computational linguistics: ACL 2023, 9978-9991, 2023 | 30 | 2023 |
| 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 | 18 | 2022 |
| Dynamical fermionization in one-dimensional spinor quantum gases SS Alam, T Skaras, L Yang, H Pu Physical Review Letters 127 (2), 023002, 2021 | 15 | 2021 |
| Scalable variational Monte Carlo with graph neural ansatz L Yang, W Hu, L Li arXiv preprint arXiv:2011.12453, 2020 | 14 | 2020 |
| 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 | 14 | 2017 |
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| 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 | 9 | 2022 |
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| 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 | 8 | 2020 |
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| Item-Language Model for Conversational Recommendation L Yang, A Subbiah, H Patel, JY Li, Y Song, R Mirghaderi, V Aggarwal arXiv preprint arXiv:2406.02844, 2024 | 5 | 2024 |
| 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 | 5 | 2022 |
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