| Deberta: Decoding-enhanced bert with disentangled attention P He, X Liu, J Gao, W Chen ICLR 2021, 2020 | 3055 | 2020 |
| On the variance of the adaptive learning rate and beyond L Liu, H Jiang, P He, W Chen, X Liu, J Gao, J Han ICLR 2019, 2019 | 2459 | 2019 |
| Multi-task deep neural networks for natural language understanding X Liu, P He, W Chen, J Gao ACL 2019, 2019 | 1504 | 2019 |
| Debertav3: Improving deberta using electra-style pre-training with gradient-disentangled embedding sharing P He, J Gao, W Chen ICLR 2023, 2021 | 1076 | 2021 |
| Instruction tuning with gpt-4 B Peng, C Li, P He, M Galley, J Gao arXiv preprint arXiv:2304.03277, 2023 | 908 | 2023 |
| Smart: Robust and efficient fine-tuning for pre-trained natural language models through principled regularized optimization H Jiang, P He, W Chen, X Liu, J Gao, T Zhao ACL 2020, 2019 | 524 | 2019 |
| Adalora: Adaptive budget allocation for parameter-efficient fine-tuning Q Zhang, M Chen, A Bukharin, N Karampatziakis, P He, Y Cheng, ... arXiv preprint arXiv:2303.10512, 2023 | 519 | 2023 |
| Check your facts and try again: Improving large language models with external knowledge and automated feedback B Peng, M Galley, P He, H Cheng, Y Xie, Y Hu, Q Huang, L Liden, Z Yu, ... arXiv preprint arXiv:2302.12813, 2023 | 453 | 2023 |
| Dola: Decoding by contrasting layers improves factuality in large language models YS Chuang, Y Xie, H Luo, Y Kim, J Glass, P He arXiv preprint arXiv:2309.03883, 2023 | 273 | 2023 |
| Diffusion-GAN: Training GANs with Diffusion Z Wang, H Zheng, P He, W Chen, M Zhou ICLR 2023, 2022 | 264 | 2022 |
| Generation-augmented retrieval for open-domain question answering Y Mao, P He, X Liu, Y Shen, J Gao, J Han, W Chen arXiv preprint arXiv:2009.08553, 2020 | 262 | 2020 |
| Query rewriting in retrieval-augmented large language models X Ma, Y Gong, P He, H Zhao, N Duan Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 245 | 2023 |
| Improving multi-task deep neural networks via knowledge distillation for natural language understanding X Liu, P He, W Chen, J Gao arXiv preprint arXiv:1904.09482, 2019 | 220 | 2019 |
| Patch diffusion: Faster and more data-efficient training of diffusion models Z Wang, Y Jiang, H Zheng, P Wang, P He, Z Wang, W Chen, M Zhou Advances in neural information processing systems 36, 72137-72154, 2023 | 214 | 2023 |
| Adversarial training for large neural language models X Liu, H Cheng, P He, W Chen, Y Wang, H Poon, J Gao arXiv preprint arXiv:2004.08994, 2020 | 199 | 2020 |
| Loftq: Lora-fine-tuning-aware quantization for large language models Y Li, Y Yu, C Liang, P He, N Karampatziakis, W Chen, T Zhao arXiv preprint arXiv:2310.08659, 2023 | 157 | 2023 |
| X-SQL: reinforce schema representation with context P He, Y Mao, K Chakrabarti, W Chen arXiv preprint arXiv:1908.08113, 2019 | 110 | 2019 |
| Truncated diffusion probabilistic models and diffusion-based adversarial auto-encoders H Zheng, P He, W Chen, M Zhou ICLR 2023, 2022 | 105* | 2022 |
| On the variance of the adaptive learning rate and beyond. arXiv 2019 L Liu, H Jiang, P He, W Chen, X Liu, J Gao, J Han arXiv preprint arXiv:1908.03265, 2019 | 105 | 2019 |
| Guiding large language models via directional stimulus prompting Z Li, B Peng, P He, M Galley, J Gao, X Yan Advances in Neural Information Processing Systems 36, 62630-62656, 2023 | 101 | 2023 |
Weizhu ChenMicrosoftBestätigte E-Mail-Adresse bei microsoft.com
