| Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning D Guo, D Yang, H Zhang, J Song, R Zhang, R Xu, Q Zhu, S Ma, P Wang, ... arXiv preprint arXiv:2501.12948, 2025 | 7507* | 2025 |
| Deepseek-v3 technical report A Liu, B Feng, B Xue, B Wang, B Wu, C Lu, C Zhao, C Deng, C Zhang, ... arXiv preprint arXiv:2412.19437, 2024 | 3676 | 2024 |
| A survey on in-context learning Q Dong, L Li, D Dai, C Zheng, J Ma, R Li, H Xia, J Xu, Z Wu, B Chang, ... EMNLP 2024, 1107-1128, 2024 | 3071 | 2024 |
| Knowledge neurons in pretrained transformers D Dai, L Dong, Y Hao, Z Sui, C Baobao, F Wei ACL 2022, 8493-8502, 2022 | 888 | 2022 |
| Deepseek llm: Scaling open-source language models with longtermism X Bi, D Chen, G Chen, S Chen, D Dai, C Deng, H Ding, K Dong, Q Du, ... arXiv preprint arXiv:2401.02954, 2024 | 784 | 2024 |
| DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model DeepSeek-AI, A Liu, B Feng, B Wang, B Wang, B Liu, C Zhao, C Dengr, ... arXiv preprint arXiv:2405.04434, 2024 | 766* | 2024 |
| Math-shepherd: Verify and reinforce llms step-by-step without human annotations P Wang, L Li, Z Shao, RX Xu, D Dai, Y Li, D Chen, Y Wu, Z Sui ACL 2024, 2024 | 756* | 2024 |
| Deepseekmoe: Towards ultimate expert specialization in mixture-of-experts language models D Dai, C Deng, C Zhao, RX Xu, H Gao, D Chen, J Li, W Zeng, X Yu, Y Wu, ... ACL 2024, 2024 | 735 | 2024 |
| 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 ACL 2023 Findings, 2023 | 613* | 2023 |
| Deepseek-vl2: Mixture-of-experts vision-language models for advanced multimodal understanding Z Wu, X Chen, Z Pan, X Liu, W Liu, D Dai, H Gao, Y Ma, C Wu, B Wang, ... arXiv preprint arXiv:2412.10302, 2024 | 515* | 2024 |
| Deepseek-coder-v2: Breaking the barrier of closed-source models in code intelligence Q Zhu, D Guo, Z Shao, D Yang, P Wang, R Xu, Y Wu, Y Li, H Gao, S Ma, ... arXiv preprint arXiv:2406.11931, 2024 | 439* | 2024 |
| DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning D Guo, D Yang, H Zhang, J Song, P Wang, Q Zhu, R Xu, R Zhang, S Ma, ... Nature 645 (8081), 633-638, 2025 | 367 | 2025 |
| Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning L Wang, L Li, D Dai, D Chen, H Zhou, F Meng, J Zhou, X Sun EMNLP 2023 Best Long Paper, 2023 | 252 | 2023 |
| Native sparse attention: Hardware-aligned and natively trainable sparse attention J Yuan, H Gao, D Dai, J Luo, L Zhao, Z Zhang, Z Xie, YX Wei, L Wang, ... ACL 2025 Best Paper, 2025 | 219* | 2025 |
| Calibrating Factual Knowledge in Pretrained Language Models Q Dong*, D Dai*, Y Song, J Xu, Z Sui, L Li EMNLP 2022 Findings, 2022 | 158 | 2022 |
| On the representation collapse of sparse mixture of experts Z Chi, L Dong, S Huang, D Dai, S Ma, B Patra, S Singhal, P Bajaj, X Song, ... NeurIPS 2022 35, 34600-34613, 2022 | 154 | 2022 |
| StableMoE: Stable Routing Strategy for Mixture of Experts D Dai, L Dong, S Ma, B Zheng, Z Sui, B Chang, F Wei ACL 2022, 2022 | 114 | 2022 |
| Preliminary study on the construction of Chinese medical knowledge graph O Byambasuren, Y Yang, Z Sui, D Dai, B Chang, S Li, H Zan Journal of Chinese Information Processing 33 (10), 1-9, 2019 | 112* | 2019 |
| Auxiliary-loss-free load balancing strategy for mixture-of-experts L Wang, H Gao, C Zhao, X Sun, D Dai arXiv preprint arXiv:2408.15664, 2024 | 92* | 2024 |
| Livebot: Generating live video comments based on visual and textual contexts S Ma, L Cui, D Dai, F Wei, X Sun AAAI 2019 33 (01), 6810-6817, 2019 | 77 | 2019 |
Zhifang SUIPeking UniversityVerified email at pku.edu.cn
