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Pengcheng He
Pengcheng He
Microsoft
Подтвержден адрес электронной почты в домене microsoft.com
Название
Процитировано
Процитировано
Год
Deberta: Decoding-enhanced bert with disentangled attention
P He, X Liu, J Gao, W Chen
ICLR 2021, 2020
28442020
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
23902019
Multi-task deep neural networks for natural language understanding
X Liu, P He, W Chen, J Gao
ACL 2019, 2019
14962019
Debertav3: Improving deberta using electra-style pre-training with gradient-disentangled embedding sharing
P He, J Gao, W Chen
ICLR 2023, 2021
9742021
Instruction tuning with gpt-4
B Peng, C Li, P He, M Galley, J Gao
arXiv preprint arXiv:2304.03277, 2023
8312023
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
5062019
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
4242023
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
4112023
Diffusion-GAN: Training GANs with Diffusion
Z Wang, H Zheng, P He, W Chen, M Zhou
ICLR 2023, 2022
2412022
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
2392020
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
2292023
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
2242019
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
1962020
Query rewriting for retrieval-augmented large language models
X Ma, Y Gong, P He, H Zhao, N Duan
arXiv preprint arXiv:2305.14283, 2023
1862023
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, 2024
1852024
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
1332023
X-SQL: reinforce schema representation with context
P He, Y Mao, K Chakrabarti, W Chen
arXiv preprint arXiv:1908.08113, 2019
1122019
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
1012019
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, 2024
872024
Platon: Pruning large transformer models with upper confidence bound of weight importance
Q Zhang, S Zuo, C Liang, A Bukharin, P He, W Chen, T Zhao
International Conference on Machine Learning, 26809-26823, 2022
852022
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