| Simcse: Simple contrastive learning of sentence embeddings T Gao, X Yao, D Chen arXiv preprint arXiv:2104.08821, 2021 | 2374 | 2021 |
| Making pre-trained language models better few-shot learners T Gao, A Fisch, D Chen arXiv preprint arXiv:2012.15723, 2020 | 1430 | 2020 |
| 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 | 565 | 2021 |
| 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 | 364 | 2019 |
| 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 | 247 | 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 | 173 | 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 | 172 | 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 | 139 | 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 | 116 | 2020 |
| Should you mask 15% in masked language modeling? A Wettig, T Gao, Z Zhong, D Chen arXiv preprint arXiv:2202.08005, 2022 | 109 | 2022 |
| 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 | 80 | 2020 |
| Enabling large language models to generate text with citations T Gao, H Yen, J Yu, D Chen arXiv preprint arXiv:2305.14627, 2023 | 78 | 2023 |
| 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 | 76 | 2020 |
| Fine-tuning language models with just forward passes S Malladi, T Gao, E Nichani, A Damian, JD Lee, D Chen, S Arora Advances in Neural Information Processing Systems 36, 2024 | 60 | 2024 |
| Sheared llama: Accelerating language model pre-training via structured pruning M Xia, T Gao, Z Zeng, D Chen arXiv preprint arXiv:2310.06694, 2023 | 51 | 2023 |
| What In-Context Learning “Learns” In-Context: Disentangling Task Recognition and Task Learning J Pan Princeton University, 2023 | 42 | 2023 |
| What In-Context Learning “Learns” In-Context: Disentangling Task Recognition and Task Learning J Pan, T Gao, H Chen, D Chen Findings of the Association for Computational Linguistics: ACL 2023, 2023 | 42 | 2023 |
| Recovering private text in federated learning of language models S Gupta, Y Huang, Z Zhong, T Gao, K Li, D Chen Advances in neural information processing systems 35, 8130-8143, 2022 | 39 | 2022 |
| 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 | 36 | 2020 |
| Evaluating large language models at evaluating instruction following Z Zeng, J Yu, T Gao, Y Meng, T Goyal, D Chen arXiv preprint arXiv:2310.07641, 2023 | 24 | 2023 |
Danqi ChenPrinceton UniversityVerified email at cs.princeton.edu
