| Simcse: Simple contrastive learning of sentence embeddings T Gao*, X Yao*, D Chen EMNLP, 2021 | 4801 | 2021 |
| Making pre-trained language models better few-shot learners T Gao*, A Fisch*, D Chen ACL, 2020 | 2493 | 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 TACL 9, 176-194, 2021 | 985 | 2021 |
| Enabling large language models to generate text with citations T Gao, H Yen, J Yu, D Chen EMNLP, 2023 | 501 | 2023 |
| Hybrid attention-based prototypical networks for noisy few-shot relation classification T Gao, X Han, Z Liu, M Sun AAAI 33 (01), 6407-6414, 2019 | 479 | 2019 |
| Sheared llama: Accelerating language model pre-training via structured pruning M Xia, T Gao, Z Zeng, D Chen ICLR, 2023 | 438 | 2023 |
| Fine-tuning language models with just forward passes S Malladi*, T Gao*, E Nichani, A Damian, JD Lee, D Chen, S Arora NeurIPS 36, 53038-53075, 2023 | 404 | 2023 |
| FewRel 2.0: Towards More Challenging Few-Shot Relation Classification T Gao, X Han, H Zhu, Z Liu, P Li, M Sun, J Zhou EMNLP, 2019 | 352 | 2019 |
| Evaluating large language models at evaluating instruction following Z Zeng, J Yu, T Gao, Y Meng, T Goyal, D Chen ICLR, 2023 | 275 | 2023 |
| Should you mask 15% in masked language modeling? A Wettig*, T Gao*, Z Zhong, D Chen EACL, 2022 | 247 | 2022 |
| 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 EMNLP, 2020 | 247 | 2020 |
| OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction X Han*, T Gao*, Y Yao, D Ye, Z Liu, M Sun EMNLP-IJCNLP: System Demonstrations, 2019 | 218 | 2019 |
| 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 AACL, 2020 | 205 | 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 | 165 | 2020 |
| 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 | 160 | 2023 |
| 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 | 137 | 2020 |
| 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 | 136 | 2022 |
| 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 | 97 | 2020 |
| How to train long-context language models (effectively) T Gao*, A Wettig*, H Yen, D Chen arXiv preprint arXiv:2410.02660, 2024 | 73 | 2024 |
| Long-context language modeling with parallel context encoding H Yen, T Gao, D Chen ACL, 2024 | 71 | 2024 |
Danqi ChenPrinceton UniversityVerified email at cs.princeton.edu
