| Why can gpt learn in-context? language models implicitly perform gradient descent as meta-optimizers D Dai, Y Sun, L Dong, Y Hao, S Ma, Z Sui, F Wei arXiv preprint arXiv:2212.10559, 2022 | 405 | 2022 |
| Retentive network: A successor to transformer for large language models Y Sun, L Dong, S Huang, S Ma, Y Xia, J Xue, J Wang, F Wei arXiv preprint arXiv:2307.08621, 2023 | 344 | 2023 |
| A length-extrapolatable transformer Y Sun, L Dong, B Patra, S Ma, S Huang, A Benhaim, V Chaudhary, ... arXiv preprint arXiv:2212.10554, 2022 | 156 | 2022 |
| Structured prompting: Scaling in-context learning to 1,000 examples Y Hao, Y Sun, L Dong, Z Han, Y Gu, F Wei arXiv preprint arXiv:2212.06713, 2022 | 53 | 2022 |
| Prototypical calibration for few-shot learning of language models Z Han, Y Hao, L Dong, Y Sun, F Wei arXiv preprint arXiv:2205.10183, 2022 | 43 | 2022 |
| You only cache once: Decoder-decoder architectures for language models Y Sun, L Dong, Y Zhu, S Huang, W Wang, S Ma, Q Zhang, J Wang, F Wei Advances in Neural Information Processing Systems 37, 7339-7361, 2025 | 41 | 2025 |
| Differential transformer T Ye, L Dong, Y Xia, Y Sun, Y Zhu, G Huang, F Wei arXiv preprint arXiv:2410.05258, 2024 | 26 | 2024 |
| Why can gpt learn incontext? language models implicitly perform gradient descent as meta-optimizers D Dai, Y Sun, L Dong, Y Hao, S Ma, Z Sui, F Wei ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation …, 2023 | 10 | 2023 |
| FocusLLM: Scaling LLM's Context by Parallel Decoding Z Li, Y Zhang, T Pan, Y Sun, Z Duan, J Fang, R Han, Z Wang, J Wang arXiv preprint arXiv:2408.11745, 2024 | 5 | 2024 |
| Multimodal Latent Language Modeling with Next-Token Diffusion Y Sun, H Bao, W Wang, Z Peng, L Dong, S Huang, J Wang, F Wei arXiv preprint arXiv:2412.08635, 2024 | 1 | 2024 |
Li DongMicrosoft ResearchПотвърден имейл адрес: microsoft.com