Simcse: Simple contrastive learning of sentence embeddings T Gao, X Yao, D Chen arXiv preprint arXiv:2104.08821, 2021 | 276 | 2021 |
Making pre-trained language models better few-shot learners T Gao, A Fisch, D Chen arXiv preprint arXiv:2012.15723, 2020 | 242 | 2020 |
Hybrid attention-based prototypical networks for noisy few-shot relation classification T Gao, X Han, Z Liu, M Sun Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6407-6414, 2019 | 163 | 2019 |
KEPLER: A unified model for knowledge embedding and pre-trained language representation X Wang, T Gao, Z Zhu, Z Zhang, Z Liu, J Li, J Tang Transactions of the Association for Computational Linguistics 9, 176-194, 2021 | 159 | 2021 |
FewRel 2.0: Towards More Challenging Few-Shot Relation Classification T Gao, X Han, H Zhu, Z Liu, P Li, M Sun, J Zhou Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 99 | 2019 |
OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction X Han, T Gao, Y Yao, D Ye, Z Liu, M Sun Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 78 | 2019 |
Learning from context or names? an empirical study on neural relation extraction H Peng, T Gao, X Han, Y Lin, P Li, Z Liu, M Sun, J Zhou arXiv preprint arXiv:2010.01923, 2020 | 57 | 2020 |
More data, more relations, more context and more openness: A review and outlook for relation extraction X Han, T Gao, Y Lin, H Peng, Y Yang, C Xiao, Z Liu, P Li, M Sun, J Zhou arXiv preprint arXiv:2004.03186, 2020 | 43 | 2020 |
Few-shot relation extraction via bayesian meta-learning on relation graphs M Qu, T Gao, LP Xhonneux, J Tang International Conference on Machine Learning, 7867-7876, 2020 | 35 | 2020 |
Neural snowball for few-shot relation learning T Gao, X Han, R Xie, Z Liu, F Lin, L Lin, M Sun Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7772-7779, 2020 | 33 | 2020 |
Continual relation learning via episodic memory activation and reconsolidation X Han, Y Dai, T Gao, Y Lin, Z Liu, P Li, M Sun, J Zhou Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 26 | 2020 |
Meta-Information Guided Meta-Learning for Few-Shot Relation Classification B Dong, Y Yao, R Xie, T Gao, X Han, Z Liu, F Lin, L Lin, M Sun Proceedings of the 28th International Conference on Computational …, 2020 | 6 | 2020 |
Manual Evaluation Matters: Reviewing Test Protocols of Distantly Supervised Relation Extraction T Gao, X Han, K Qiu, Y Bai, Z Xie, Y Lin, Z Liu, P Li, M Sun, J Zhou arXiv preprint arXiv:2105.09543, 2021 | 5 | 2021 |
Should You Mask 15% in Masked Language Modeling? A Wettig, T Gao, Z Zhong, D Chen arXiv preprint arXiv:2202.08005, 2022 | 1 | 2022 |
Ditch the Gold Standard: Re-evaluating Conversational Question Answering H Li, T Gao, M Goenka, D Chen arXiv preprint arXiv:2112.08812, 2021 | 1 | 2021 |
Recovering Private Text in Federated Learning of Language Models S Gupta, Y Huang, Z Zhong, T Gao, K Li, D Chen arXiv preprint arXiv:2205.08514, 2022 | | 2022 |
More data, more relations, more context and more openness: A review and outlook for relation extraction Open Website X Han, T Gao, Y Lin, H Peng | | |
OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction Open Website X Han, T Gao, Y Yao, D Ye, Z Liu, M Sun | | |
KEPLER: A unified model for knowledge embedding and pre-trained language representation Open Website X Wang, T Gao, Z Zhu, Z Zhang, Z Liu, J Li, J Tang | | |
Learning from context or names? an empirical study on neural relation extraction Open Website H Peng, T Gao, X Han, Y Lin, P Li, Z Liu, M Sun, J Zhou | | |