| Lima: Less is more for alignment C Zhou, P Liu, P Xu, S Iyer, J Sun, Y Mao, X Ma, A Efrat, P Yu, L Yu, ... Advances in Neural Information Processing Systems 36, 2024 | 400 | 2024 |
| Self-alignment with instruction backtranslation X Li, P Yu, C Zhou, T Schick, L Zettlemoyer, O Levy, J Weston, M Lewis arXiv preprint arXiv:2308.06259, 2023 | 73 | 2023 |
| Opt-iml: Scaling language model instruction meta learning through the lens of generalization S Iyer, XV Lin, R Pasunuru, T Mihaylov, D Simig, P Yu, K Shuster, T Wang, ... arXiv preprint arXiv:2212.12017, 2022 | 62 | 2022 |
| Learning diverse stochastic human-action generators by learning smooth latent transitions Z Wang, P Yu, Y Zhao, R Zhang, Y Zhou, J Yuan, C Chen Proceedings of the AAAI conference on artificial intelligence 34 (07), 12281 …, 2020 | 42 | 2020 |
| Feature quantization improves gan training Y Zhao, C Li, P Yu, J Gao, C Chen arXiv preprint arXiv:2004.02088, 2020 | 38 | 2020 |
| Structure-aware human-action generation P Yu, Y Zhao, C Li, J Yuan, C Chen Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 37 | 2020 |
| Shepherd: A critic for language model generation T Wang, P Yu, XE Tan, S O'Brien, R Pasunuru, J Dwivedi-Yu, ... arXiv preprint arXiv:2308.04592, 2023 | 26 | 2023 |
| Bayesian meta sampling for fast uncertainty adaptation Z Wang, Y Zhao, P Yu, R Zhang, C Chen International Conference on Learning Representations, 2019 | 20 | 2019 |
| Alert: Adapting language models to reasoning tasks P Yu, T Wang, O Golovneva, B AlKhamissi, S Verma, Z Jin, G Ghosh, ... arXiv preprint arXiv:2212.08286, 2022 | 12 | 2022 |
| Efficient language modeling with sparse all-mlp P Yu, M Artetxe, M Ott, S Shleifer, H Gong, V Stoyanov, X Li arXiv preprint arXiv:2203.06850, 2022 | 11 | 2022 |
| The art of llm refinement: Ask, refine, and trust K Shridhar, K Sinha, A Cohen, T Wang, P Yu, R Pasunuru, M Sachan, ... arXiv preprint arXiv:2311.07961, 2023 | 9 | 2023 |
| Remp: Rectified metric propagation for few-shot learning Y Zhao, C Li, P Yu, C Chen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 8 | 2021 |
| OPT-R: Exploring the Role of Explanations in Finetuning and Prompting for Reasoning Skills of Large Language Models B AlKhamissi, S Verma, P Yu, Z Jin, A Celikyilmaz, M Diab arXiv preprint arXiv:2305.12001, 2023 | 5 | 2023 |
| Rethinking sentiment style transfer P Yu, Y Zhao, C Li, C Chen Findings of the Association for Computational Linguistics: EMNLP 2021, 1569-1582, 2021 | 5 | 2021 |
| Improve variational autoencoder for text generationwith discrete latent bottleneck Y Zhao, P Yu, S Mahapatra, Q Su, C Chen arXiv preprint arXiv:2004.10603, 2020 | 5 | 2020 |
| Improve variational autoencoder for text generation with discrete latent bottleneck Y Zhao, P Yu, S Mahapatra, Q Su, C Chen arXiv preprint arXiv:2004.10603, 2020 | 5 | 2020 |
| Low-power wireless sensor network protocol of mobile health based on IPv6 L Wang, S Hao, P Yu, Z Huang 2016 35th Chinese Control Conference (CCC), 8479-8484, 2016 | 5 | 2016 |
| LIMA: less is more for alignment (2023) C Zhou, P Liu, P Xu, S Iyer, J Sun, Y Mao, X Ma, A Efrat, P Yu, L Yu, ... WARNING: APPENDIX Ccontains EXAMPLES OF TOXIC USER INPUTS, WHICH MAY INCLUDE …, 0 | 5 | |
| SDA: Improving text generation with self data augmentation P Yu, R Zhang, Y Zhao, Y Zhang, C Li, C Chen arXiv preprint arXiv:2101.03236, 2021 | 4 | 2021 |
| Discretized Bottleneck: Posterior-Collapse-Free Sequence-to-Sequence Learning Y Zhao, P Yu, S Mahapatra, Q Su, C Chen | 4 | 2020 |
Yang ZhaoGoogleПотвърден имейл адрес: google.com
