| On the variance of the adaptive learning rate and beyond L Liu, H Jiang, P He, W Chen, X Liu, J Gao, J Han Proceedings of the Eighth International Conference on Learning …, 2019 | 2473 | 2019 |
| Phi-3 technical report: A highly capable language model locally on your phone M Abdin, J Aneja, H Awadalla, A Awadallah, AA Awan, N Bach, A Bahree, ... arXiv preprint arXiv:2404.14219, 2024 | 881 | 2024 |
| Empower sequence labeling with task-aware neural language model L Liu, J Shang, F Xu, X Ren, H Gui, J Peng, J Han Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence …, 2018 | 457 | 2018 |
| Understanding the difficulty of training transformers L Liu, X Liu, J Gao, W Chen, J Han Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 313 | 2020 |
| Learning named entity tagger using domain-specific dictionary J Shang*, L Liu*, X Ren, X Gu, T Ren, J Han Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 264 | 2018 |
| Model tells you what to discard: Adaptive kv cache compression for llms S Ge, Y Zhang, L Liu, M Zhang, J Han, J Gao arXiv preprint arXiv:2310.01801, 2023 | 165 | 2023 |
| Triovecevent: Embedding-based online local event detection in geo-tagged tweet streams C Zhang, L Liu, D Lei, Q Yuan, H Zhuang, T Hanratty, J Han Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 149 | 2017 |
| Very deep transformers for neural machine translation X Liu, K Duh, L Liu, J Gao arXiv preprint arXiv:2008.07772, 2020 | 137 | 2020 |
| Crossweigh: Training named entity tagger from imperfect annotations Z Wang*, J Shang*, L Liu*, L Lu, J Liu, J Han Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 123 | 2019 |
| Community detection based on structure and content: A content propagation perspective L Liu, L Xu, Z Wangy, E Chen Proceedings of the 2015 IEEE International Conference on Data Mining (ICDM …, 2015 | 88 | 2015 |
| Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach L Liu*, X Ren*, Q Zhu, S Zhi, H Gui, H Ji, J Han Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 87 | 2017 |
| Cross-relation cross-bag attention for distantly-supervised relation extraction Y Yuan, L Liu, S Tang, Z Zhang, Y Zhuang, S Pu, F Wu, X Ren Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence …, 2019 | 74 | 2019 |
| Nettaxo: Automated topic taxonomy construction from text-rich network J Shang, X Zhang, L Liu, S Li, J Han Proceedings of the web conference 2020, 1908-1919, 2020 | 68 | 2020 |
| On the transformer growth for progressive bert training X Gu, L Liu, H Yu, J Li, C Chen, J Han arXiv preprint arXiv:2010.12562, 2020 | 61 | 2020 |
| Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling L Liu, X Ren, J Shang, J Peng, J Han Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 56 | 2018 |
| On the variance of the adaptive learning rate and beyond (2019) L Liu, H Jiang, P He, W Chen, X Liu, J Gao, J Han arXiv preprint arXiv:1908.03265, 1908 | 50 | 1908 |
| Multi-head or single-head? an empirical comparison for transformer training L Liu, J Liu, J Han arXiv preprint arXiv:2106.09650, 2021 | 47 | 2021 |
| Towards adaptive residual network training: A neural-ode perspective C Dong, L Liu, Z Li, J Shang International conference on machine learning, 2616-2626, 2020 | 44 | 2020 |
| Ucphrase: Unsupervised context-aware quality phrase tagging X Gu, Z Wang, Z Bi, Y Meng, L Liu, J Han, J Shang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 40 | 2021 |
| Tell your model where to attend: Post-hoc attention steering for llms Q Zhang, C Singh, L Liu, X Liu, B Yu, J Gao, T Zhao arXiv preprint arXiv:2311.02262, 2023 | 33 | 2023 |
Jiawei HanAbel Bliss Professor of Computer Science, University of IllinoisПотвърден имейл адрес: cs.uiuc.edu